Condition Data-frame.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>date</th>\n",
       "      <th>activity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2003-05-07 12:00:00</td>\n",
       "      <td>2003-05-07</td>\n",
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       "      <th>1</th>\n",
       "      <td>2003-05-07 12:01:00</td>\n",
       "      <td>2003-05-07</td>\n",
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       "      <th>2</th>\n",
       "      <td>2003-05-07 12:02:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>0</td>\n",
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       "      <td>2003-05-07 12:03:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>20</td>\n",
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       "      <th>4</th>\n",
       "      <td>2003-05-07 12:04:00</td>\n",
       "      <td>2003-05-07</td>\n",
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       "                 timestamp        date  activity\n",
       "0      2003-05-07 12:00:00  2003-05-07         0\n",
       "1      2003-05-07 12:01:00  2003-05-07       143\n",
       "2      2003-05-07 12:02:00  2003-05-07         0\n",
       "3      2003-05-07 12:03:00  2003-05-07        20\n",
       "4      2003-05-07 12:04:00  2003-05-07       166\n",
       "...                    ...         ...       ...\n",
       "23239  2003-05-23 15:19:00  2003-05-23         0\n",
       "23240  2003-05-23 15:20:00  2003-05-23         0\n",
       "23241  2003-05-23 15:21:00  2003-05-23         0\n",
       "23242  2003-05-23 15:22:00  2003-05-23         0\n",
       "23243  2003-05-23 15:23:00  2003-05-23       533\n",
       "\n",
       "[23244 rows x 3 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df= pd.read_csv('condition_1.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "timestamp    object\n",
       "date         object\n",
       "activity      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#only taking a 7 day motor activity reading per patient\n",
    "my_df= df.drop(df.index[0: 720])\n",
    "\n",
    "#starting patient 1 from 12:00am \n",
    "my_df= my_df.drop(df.index[10800:23245])\n",
    "\n",
    "#creating an ID tag for patient 1\n",
    "\n",
    "my_df['Id'] =np.nan\n",
    "my_df['Id'].fillna('condition_1', inplace= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    }
   ],
   "source": [
    "def load_hourly_activity(frame):\n",
    "    my_df['total_hour_activity'] = np.nan\n",
    "    my_df['timestamp'] = my_df['timestamp'].astype(str)\n",
    "    \n",
    "    frame['timestamp'] = pd.to_datetime(frame.timestamp)\n",
    "    frame['timestamp']= frame['timestamp'].dt.strftime('%H:%M')\n",
    "    \n",
    "    #adding the total of each hour and putting the values in a new column\n",
    "    list = []\n",
    "    score = 0;\n",
    "    for i, row in frame.iterrows():\n",
    "        activity = i\n",
    "        score = score + row['activity']\n",
    "        if (i + 1) % 60 == 0:\n",
    "            list.append(score)\n",
    "            score = 0\n",
    "            \n",
    "    goodTimes = frame[frame['timestamp'].str.endswith(\":00\")]\n",
    "    frame = goodTimes   \n",
    "    frame.reset_index(inplace = True)\n",
    "    frame['total_hour_activity'] = list\n",
    "    frame = frame.drop(['index', 'activity'], axis =1)\n",
    "    \n",
    "    frame_t = frame.T\n",
    "    header_row = 0\n",
    "    frame_t.columns = frame_t.iloc[header_row]\n",
    "    frame_t = frame_t.drop('timestamp')\n",
    "    frame_t = frame_t.drop('Id')\n",
    "    frame_t = frame_t.drop('date')\n",
    "    frame_t = frame_t.reset_index(drop = True)\n",
    "    frame_t['Id'] =np.nan\n",
    "    frame_t['Id'].fillna('condition', inplace= True)\n",
    "    frame =frame_t\n",
    "    return frame\n",
    "\n",
    "one_df = load_hourly_activity(my_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "timestamp 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00  ...  \\\n",
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       "\n",
       "timestamp  15:00  16:00  17:00  18:00  19:00 20:00  21:00  22:00 23:00  Id  \n",
       "0          11541  28862  20981  14789  10792  5493  12413  11248  4485 NaN  \n",
       "\n",
       "[1 rows x 169 columns]"
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "one_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    },
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       "timestamp  ...  15:00  16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00  Id  \n",
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     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "two_df= pd.read_csv('condition_2.csv')\n",
    "two_df= two_df.drop(two_df.index[0: 540])\n",
    "two_df= two_df.drop(two_df.index[10080: 38927])\n",
    "two_df['Id'] =np.nan\n",
    "two_df['Id'].fillna('condition_2', inplace= True)\n",
    "two_df = load_hourly_activity(two_df)\n",
    "two_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    },
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       "timestamp 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00  09:00  ...  \\\n",
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       "\n",
       "timestamp  15:00  16:00  17:00  18:00  19:00  20:00  21:00 22:00  23:00  Id  \n",
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     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "three_df= pd.read_csv('condition_3.csv')\n",
    "three_df= three_df.drop(three_df.index[0: 540])\n",
    "three_df= three_df.drop(three_df.index[10080: 38927])\n",
    "three_df['Id'] =np.nan\n",
    "three_df['Id'].fillna('condition_3', inplace= True)\n",
    "three_df = load_hourly_activity(three_df)  \n",
    "three_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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   "source": [
    "four_df= pd.read_csv('condition_4.csv')\n",
    "four_df= four_df.drop(four_df.index[0: 721])\n",
    "four_df= four_df.drop(four_df.index[10080: 38927])\n",
    "four_df['Id'] =np.nan\n",
    "four_df['Id'].fillna('condition_4', inplace= True)\n",
    "four_df = load_hourly_activity(four_df)  \n",
    "four_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "execution_count": 10,
     "metadata": {},
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   "source": [
    "five_df= pd.read_csv('condition_5.csv')\n",
    "five_df= five_df.drop(five_df.index[0: 810])\n",
    "five_df= five_df.drop(five_df.index[10080: 21494])\n",
    "five_df['Id'] =np.nan\n",
    "five_df['Id'].fillna('condition_5', inplace= True)\n",
    "five_df = load_hourly_activity(five_df)  \n",
    "five_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "six_df= pd.read_csv('condition_6.csv')\n",
    "six_df= six_df.drop(six_df.index[0: 720])\n",
    "six_df= six_df.drop(six_df.index[10080: 21494])\n",
    "six_df['Id'] =np.nan\n",
    "six_df['Id'].fillna('condition_6', inplace = True)\n",
    "six_df = load_hourly_activity(six_df) \n",
    "six_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 12,
     "metadata": {},
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   ],
   "source": [
    "seven_df= pd.read_csv('condition_7.csv')\n",
    "seven_df= seven_df.drop(seven_df.index[0: 840])\n",
    "seven_df= seven_df.drop(seven_df.index[10080: 21494])\n",
    "seven_df['Id'] =np.nan\n",
    "seven_df['Id'].fillna('condition_7', inplace = True)\n",
    "seven_df = load_hourly_activity(seven_df) \n",
    "seven_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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    },
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 169 columns</p>\n",
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      ],
      "text/plain": [
       "timestamp 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00  ...  \\\n",
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       "\n",
       "timestamp 15:00  16:00  17:00 18:00  19:00  20:00  21:00 22:00 23:00  Id  \n",
       "0          8501  21184  18112  2210  15867  10080  10080  7826  2130 NaN  \n",
       "\n",
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      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eight_df= pd.read_csv('condition_8.csv')\n",
    "eight_df= eight_df.drop(eight_df.index[0: 840])\n",
    "eight_df= eight_df.drop(eight_df.index[10080: 21494])\n",
    "eight_df['Id'] =np.nan\n",
    "eight_df['Id'].fillna('condition_8', inplace= True)\n",
    "eight_df = load_hourly_activity(eight_df)\n",
    "eight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
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     "metadata": {},
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   ],
   "source": [
    "nine_df= pd.read_csv('condition_9.csv')\n",
    "nine_df= nine_df.drop(nine_df.index[0: 690])\n",
    "nine_df= nine_df.drop(nine_df.index[10080: 21494])\n",
    "nine_df['Id'] =np.nan\n",
    "nine_df['Id'].fillna('condition_9', inplace = True)\n",
    "nine_df = load_hourly_activity(nine_df)\n",
    "nine_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "metadata": {},
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   ],
   "source": [
    "ten_df= pd.read_csv('condition_10.csv')\n",
    "ten_df= ten_df.drop(ten_df.index[0: 900])\n",
    "ten_df= ten_df.drop(ten_df.index[10080: 21494])\n",
    "ten_df['Id'] =np.nan\n",
    "ten_df['Id'].fillna('condition_10', inplace= True)\n",
    "ten_df = load_hourly_activity(ten_df)\n",
    "ten_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
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       "timestamp 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00  ...  \\\n",
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       "\n",
       "timestamp 15:00 16:00  17:00  18:00  19:00  20:00  21:00 22:00 23:00  Id  \n",
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     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "eleven_df= pd.read_csv('condition_11.csv')\n",
    "eleven_df= eleven_df.drop(eleven_df.index[0: 870])\n",
    "eleven_df= eleven_df.drop(eleven_df.index[10080: 22990])\n",
    "eleven_df['Id'] =np.nan\n",
    "eleven_df['Id'].fillna('condition_11', inplace = True)\n",
    "eleven_df = load_hourly_activity(eleven_df)\n",
    "eleven_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    },
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     "execution_count": 17,
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   ],
   "source": [
    "twelve_df= pd.read_csv('condition_12.csv')\n",
    "twelve_df= twelve_df.drop(twelve_df.index[0: 840])\n",
    "twelve_df= twelve_df.drop(twelve_df.index[10080: 22990])\n",
    "twelve_df['Id'] =np.nan\n",
    "twelve_df['Id'].fillna('condition_12', inplace = True)\n",
    "twelve_df = load_hourly_activity(twelve_df)\n",
    "twelve_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "execution_count": 18,
     "metadata": {},
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   ],
   "source": [
    "thirteen_df= pd.read_csv('condition_13.csv')\n",
    "thirteen_df= thirteen_df.drop(thirteen_df.index[0: 900])\n",
    "thirteen_df= thirteen_df.drop(thirteen_df.index[10080: 25991])\n",
    "thirteen_df['Id'] =np.nan\n",
    "thirteen_df['Id'].fillna('condition_13', inplace= True)\n",
    "thirteen_df = load_hourly_activity(thirteen_df)\n",
    "thirteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "metadata": {},
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   "source": [
    "fourteen_df = pd.read_csv(\"condition_14.csv\")\n",
    "fourteen_df= fourteen_df.drop(fourteen_df.index[0: 810])\n",
    "fourteen_df= fourteen_df.drop(fourteen_df.index[10080: 25991])\n",
    "fourteen_df['Id'] =np.nan\n",
    "fourteen_df['Id'].fillna('condition_14', inplace= True)\n",
    "fourteen_df = load_hourly_activity(fourteen_df)\n",
    "fourteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 20,
     "metadata": {},
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   "source": [
    "fifteen_df = pd.read_csv(\"condition_15.csv\")\n",
    "fifteen_df= fifteen_df.drop(fifteen_df.index[0: 840])\n",
    "fifteen_df= fifteen_df.drop(fifteen_df.index[10080: 25991])\n",
    "fifteen_df['Id'] =np.nan\n",
    "fifteen_df['Id'].fillna('condition_15', inplace= True)\n",
    "fifteen_df = load_hourly_activity(fifteen_df)\n",
    "fifteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "sixteen_df = pd.read_csv(\"condition_16.csv\")\n",
    "sixteen_df= sixteen_df.drop(sixteen_df.index[0: 840])\n",
    "sixteen_df= sixteen_df.drop(sixteen_df.index[10080: 41848])\n",
    "sixteen_df['Id'] =np.nan\n",
    "sixteen_df['Id'].fillna('condition_16', inplace= True)\n",
    "sixteen_df = load_hourly_activity(sixteen_df)\n",
    "sixteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    },
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       "      <td>NaN</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 169 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp  00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00  ...  \\\n",
       "0          10407   813   383   897   581   314   604   383    30  1682  ...   \n",
       "\n",
       "timestamp  15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00  Id  \n",
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       "\n",
       "[1 rows x 169 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seventeen_df = pd.read_csv(\"condition_17.csv\")\n",
    "seventeen_df= seventeen_df.drop(seventeen_df.index[0: 870])\n",
    "seventeen_df= seventeen_df.drop(seventeen_df.index[10080: 41848])\n",
    "seventeen_df['Id'] =np.nan\n",
    "seventeen_df['Id'].fillna('condition_17', inplace= True)\n",
    "seventeen_df = load_hourly_activity(seventeen_df)\n",
    "seventeen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 23,
     "metadata": {},
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   ],
   "source": [
    "eighteen_df = pd.read_csv(\"condition_18.csv\")\n",
    "eighteen_df= eighteen_df.drop(eighteen_df.index[0: 690])\n",
    "eighteen_df= eighteen_df.drop(eighteen_df.index[10080: 41848])\n",
    "eighteen_df['Id'] =np.nan\n",
    "eighteen_df['Id'].fillna('condition_18', inplace= True)\n",
    "eighteen_df = load_hourly_activity(eighteen_df)\n",
    "eighteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
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     "execution_count": 24,
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   ],
   "source": [
    "nineteen_df = pd.read_csv(\"condition_19.csv\")\n",
    "nineteen_df= nineteen_df.drop(nineteen_df.index[0: 570])\n",
    "nineteen_df= nineteen_df.drop(nineteen_df.index[10080: 41848])\n",
    "nineteen_df['Id'] =np.nan\n",
    "nineteen_df['Id'].fillna('condition_19', inplace= True)\n",
    "nineteen_df = load_hourly_activity(nineteen_df)\n",
    "nineteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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      "text/plain": [
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       "timestamp 15:00  16:00 17:00 18:00  19:00 20:00  21:00 22:00 23:00  Id  \n",
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     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "twenty_df = pd.read_csv(\"condition_20.csv\")\n",
    "twenty_df= twenty_df.drop(twenty_df.index[0: 750])\n",
    "twenty_df= twenty_df.drop(twenty_df.index[10080: 41848])\n",
    "twenty_df['Id'] =np.nan\n",
    "twenty_df['Id'].fillna('condition_20', inplace= True)\n",
    "twenty_df = load_hourly_activity(twenty_df)\n",
    "twenty_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 21"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "0          19489  9572  6183  11933  2118  8042  6048  4028     8 NaN  \n",
       "\n",
       "[1 rows x 169 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twentyone_df = pd.read_csv(\"condition_21.csv\")\n",
    "twentyone_df= twentyone_df.drop(twentyone_df.index[0: 625])\n",
    "twentyone_df= twentyone_df.drop(twentyone_df.index[10080: 41848])\n",
    "twentyone_df['Id'] =np.nan\n",
    "twentyone_df['Id'].fillna('condition_21', inplace= True)\n",
    "twentyone_df = load_hourly_activity(twentyone_df)\n",
    "twentyone_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
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     "execution_count": 27,
     "metadata": {},
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   ],
   "source": [
    "twentytwo_df = pd.read_csv(\"condition_22.csv\")\n",
    "twentytwo_df= twentytwo_df.drop(twentytwo_df.index[0: 795])\n",
    "twentytwo_df= twentytwo_df.drop(twentytwo_df.index[10080: 41848])\n",
    "twentytwo_df['Id'] =np.nan\n",
    "twentytwo_df['Id'].fillna('condition_22', inplace= True)\n",
    "twentytwo_df = load_hourly_activity(twentytwo_df)\n",
    "twentytwo_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condition 23"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 28,
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   ],
   "source": [
    "twentythree_df = pd.read_csv(\"condition_23.csv\")\n",
    "twentythree_df= twentythree_df.drop(twentythree_df.index[0: 660])\n",
    "twentythree_df= twentythree_df.drop(twentythree_df.index[10080: 41848])\n",
    "twentythree_df['Id'] =np.nan\n",
    "twentythree_df['Id'].fillna('condition_23', inplace= True)\n",
    "twentythree_df= load_hourly_activity(twentythree_df)\n",
    "twentythree_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_frames = [one_df,two_df, three_df, four_df, five_df, six_df, seven_df, eight_df, nine_df, ten_df, eleven_df, twelve_df, thirteen_df,\n",
    "             fourteen_df, fifteen_df, sixteen_df, seventeen_df, eighteen_df, nineteen_df, twenty_df, twentyone_df, twentytwo_df,\n",
    "             twentythree_df]\n",
    "condition_df = pd.concat(all_frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "      <td>33830</td>\n",
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       "      <td>18419</td>\n",
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       "      <th>0</th>\n",
       "      <td>4126</td>\n",
       "      <td>135</td>\n",
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       "      <td>251</td>\n",
       "      <td>299</td>\n",
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       "      <td>9466</td>\n",
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       "      <td>858</td>\n",
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       "      <td>17556</td>\n",
       "      <td>15250</td>\n",
       "      <td>12628</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>606</td>\n",
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       "      <td>1176</td>\n",
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       "      <td>31715</td>\n",
       "      <td>18786</td>\n",
       "      <td>14797</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>112</td>\n",
       "      <td>340</td>\n",
       "      <td>10844</td>\n",
       "      <td>14721</td>\n",
       "      <td>8324</td>\n",
       "      <td>6310</td>\n",
       "      <td>26737</td>\n",
       "      <td>16852</td>\n",
       "      <td>5452</td>\n",
       "      <td>589</td>\n",
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       "      <td>2724</td>\n",
       "      <td>1933</td>\n",
       "      <td>118</td>\n",
       "      <td>3679</td>\n",
       "      <td>3587</td>\n",
       "      <td>178</td>\n",
       "      <td>148</td>\n",
       "      <td>2840</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1078</td>\n",
       "      <td>224</td>\n",
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       "      <td>810</td>\n",
       "      <td>676</td>\n",
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       "      <td>43040</td>\n",
       "      <td>26806</td>\n",
       "      <td>12270</td>\n",
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       "      <td>633</td>\n",
       "      <td>669</td>\n",
       "      <td>23893</td>\n",
       "      <td>5787</td>\n",
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       "      <td>2154</td>\n",
       "      <td>8280</td>\n",
       "      <td>8312</td>\n",
       "      <td>5281</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>185</td>\n",
       "      <td>65</td>\n",
       "      <td>233</td>\n",
       "      <td>435</td>\n",
       "      <td>34</td>\n",
       "      <td>110</td>\n",
       "      <td>97</td>\n",
       "      <td>516</td>\n",
       "      <td>17279</td>\n",
       "      <td>6196</td>\n",
       "      <td>...</td>\n",
       "      <td>6152</td>\n",
       "      <td>20672</td>\n",
       "      <td>15809</td>\n",
       "      <td>35751</td>\n",
       "      <td>30866</td>\n",
       "      <td>4359</td>\n",
       "      <td>5973</td>\n",
       "      <td>5071</td>\n",
       "      <td>23938</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10407</td>\n",
       "      <td>813</td>\n",
       "      <td>383</td>\n",
       "      <td>897</td>\n",
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       "      <td>314</td>\n",
       "      <td>604</td>\n",
       "      <td>383</td>\n",
       "      <td>30</td>\n",
       "      <td>1682</td>\n",
       "      <td>...</td>\n",
       "      <td>13615</td>\n",
       "      <td>7349</td>\n",
       "      <td>3011</td>\n",
       "      <td>6775</td>\n",
       "      <td>8720</td>\n",
       "      <td>8566</td>\n",
       "      <td>2726</td>\n",
       "      <td>4785</td>\n",
       "      <td>4848</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2732</td>\n",
       "      <td>5053</td>\n",
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       "      <td>5050</td>\n",
       "      <td>414</td>\n",
       "      <td>82</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>122</td>\n",
       "      <td>280</td>\n",
       "      <td>399</td>\n",
       "      <td>607</td>\n",
       "      <td>284</td>\n",
       "      <td>580</td>\n",
       "      <td>9617</td>\n",
       "      <td>8456</td>\n",
       "      <td>6791</td>\n",
       "      <td>6327</td>\n",
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       "      <td>12957</td>\n",
       "      <td>3020</td>\n",
       "      <td>22446</td>\n",
       "      <td>23009</td>\n",
       "      <td>25131</td>\n",
       "      <td>42037</td>\n",
       "      <td>7524</td>\n",
       "      <td>12550</td>\n",
       "      <td>5624</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
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       "      <td>340</td>\n",
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       "      <td>260</td>\n",
       "      <td>2345</td>\n",
       "      <td>6019</td>\n",
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       "      <td>2815</td>\n",
       "      <td>10402</td>\n",
       "      <td>6141</td>\n",
       "      <td>7420</td>\n",
       "      <td>25923</td>\n",
       "      <td>1581</td>\n",
       "      <td>11264</td>\n",
       "      <td>5600</td>\n",
       "      <td>1088</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>155</td>\n",
       "      <td>145</td>\n",
       "      <td>354</td>\n",
       "      <td>126</td>\n",
       "      <td>124</td>\n",
       "      <td>120</td>\n",
       "      <td>624</td>\n",
       "      <td>241</td>\n",
       "      <td>804</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>19489</td>\n",
       "      <td>9572</td>\n",
       "      <td>6183</td>\n",
       "      <td>11933</td>\n",
       "      <td>2118</td>\n",
       "      <td>8042</td>\n",
       "      <td>6048</td>\n",
       "      <td>4028</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>804</td>\n",
       "      <td>1335</td>\n",
       "      <td>126</td>\n",
       "      <td>4253</td>\n",
       "      <td>1318</td>\n",
       "      <td>926</td>\n",
       "      <td>1901</td>\n",
       "      <td>4419</td>\n",
       "      <td>654</td>\n",
       "      <td>210</td>\n",
       "      <td>...</td>\n",
       "      <td>27403</td>\n",
       "      <td>13590</td>\n",
       "      <td>23345</td>\n",
       "      <td>6162</td>\n",
       "      <td>23579</td>\n",
       "      <td>16382</td>\n",
       "      <td>6956</td>\n",
       "      <td>5749</td>\n",
       "      <td>389</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>511</td>\n",
       "      <td>2325</td>\n",
       "      <td>580</td>\n",
       "      <td>2808</td>\n",
       "      <td>0</td>\n",
       "      <td>1677</td>\n",
       "      <td>307</td>\n",
       "      <td>3043</td>\n",
       "      <td>1769</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>22059</td>\n",
       "      <td>48563</td>\n",
       "      <td>18268</td>\n",
       "      <td>35373</td>\n",
       "      <td>27431</td>\n",
       "      <td>32513</td>\n",
       "      <td>20643</td>\n",
       "      <td>16746</td>\n",
       "      <td>30018</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 169 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp  00:00 01:00  02:00  03:00 04:00  05:00  06:00  07:00  08:00  09:00  \\\n",
       "0            480   245    424    242   733     58    600    822   8804   6687   \n",
       "0           1532  1535    546    270  5704   9447  28610  19627  24468  30029   \n",
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       "0           4594   175    612    192   705    950    307  17239  14846   6839   \n",
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       "0           1386   818   2135    974   241   1026   1812    688   1343   3193   \n",
       "0           2882   871    411   2840  1243    506   1093  11200  21471  25424   \n",
       "0            959   328   1629    641   440    548    346  12782  31878  24143   \n",
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       "0            706  2978    662     47   383    643   4018   5668   4839   3091   \n",
       "0            304   606    316   2275  4103  16187  14692   8681   1295   1176   \n",
       "0            112   340  10844  14721  8324   6310  26737  16852   5452    589   \n",
       "0           1078   224   1091    209   810    676   1440  43040  26806  12270   \n",
       "0            185    65    233    435    34    110     97    516  17279   6196   \n",
       "0          10407   813    383    897   581    314    604    383     30   1682   \n",
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       "0            122   280    399    607   284    580   9617   8456   6791   6327   \n",
       "0              0     0     69    163   535    340    518    260   2345   6019   \n",
       "0            155   145    354    126   124    120    624    241    804     13   \n",
       "0            804  1335    126   4253  1318    926   1901   4419    654    210   \n",
       "0            511  2325    580   2808     0   1677    307   3043   1769   2015   \n",
       "\n",
       "timestamp  ...  15:00  16:00  17:00  18:00  19:00  20:00  21:00  22:00  23:00  \\\n",
       "0          ...  11541  28862  20981  14789  10792   5493  12413  11248   4485   \n",
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       "0          ...  29577  27588  14077  16752  21303   7542  23354  28496  11572   \n",
       "0          ...    843  24311  32880  38987  17614  21216  33127  14813  14132   \n",
       "0          ...   8501  21184  18112   2210  15867  10080  10080   7826   2130   \n",
       "0          ...   5771  13326   6142  27368  16076   5530  24348   9677   6113   \n",
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       "0          ...  39653  26809  14177  15706  13799  24882  31715  18786  14797   \n",
       "0          ...   2724   1933    118   3679   3587    178    148   2840      0   \n",
       "0          ...    633    669  23893   5787   5744   2154   8280   8312   5281   \n",
       "0          ...   6152  20672  15809  35751  30866   4359   5973   5071  23938   \n",
       "0          ...  13615   7349   3011   6775   8720   8566   2726   4785   4848   \n",
       "0          ...  10505   6546   4641   5641  14100   5129   5050    414     82   \n",
       "0          ...  12957   3020  22446  23009  25131  42037   7524  12550   5624   \n",
       "0          ...   2815  10402   6141   7420  25923   1581  11264   5600   1088   \n",
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       "0          ...  27403  13590  23345   6162  23579  16382   6956   5749    389   \n",
       "0          ...  22059  48563  18268  35373  27431  32513  20643  16746  30018   \n",
       "\n",
       "timestamp  Id  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "0         NaN  \n",
       "\n",
       "[23 rows x 169 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "condition_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#condition_df.to_csv('condition_dataframe.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_df = pd.read_csv('condition_wide_dataframe.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>632</td>\n",
       "      <td>356</td>\n",
       "      <td>5879</td>\n",
       "      <td>2537</td>\n",
       "      <td>1537</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>4408</td>\n",
       "      <td>2075</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>485</td>\n",
       "      <td>...</td>\n",
       "      <td>33605</td>\n",
       "      <td>42409</td>\n",
       "      <td>30456</td>\n",
       "      <td>19506</td>\n",
       "      <td>26851</td>\n",
       "      <td>20286</td>\n",
       "      <td>11681</td>\n",
       "      <td>2561</td>\n",
       "      <td>19681</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>2220</td>\n",
       "      <td>423</td>\n",
       "      <td>203</td>\n",
       "      <td>28</td>\n",
       "      <td>569</td>\n",
       "      <td>388</td>\n",
       "      <td>11980</td>\n",
       "      <td>17591</td>\n",
       "      <td>16399</td>\n",
       "      <td>...</td>\n",
       "      <td>35779</td>\n",
       "      <td>24143</td>\n",
       "      <td>52504</td>\n",
       "      <td>44385</td>\n",
       "      <td>43854</td>\n",
       "      <td>30383</td>\n",
       "      <td>26798</td>\n",
       "      <td>4657</td>\n",
       "      <td>8929</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4835</td>\n",
       "      <td>3959</td>\n",
       "      <td>6457</td>\n",
       "      <td>807</td>\n",
       "      <td>1710</td>\n",
       "      <td>360</td>\n",
       "      <td>532</td>\n",
       "      <td>544</td>\n",
       "      <td>949</td>\n",
       "      <td>...</td>\n",
       "      <td>13525</td>\n",
       "      <td>21183</td>\n",
       "      <td>12676</td>\n",
       "      <td>10663</td>\n",
       "      <td>8813</td>\n",
       "      <td>9488</td>\n",
       "      <td>5794</td>\n",
       "      <td>3055</td>\n",
       "      <td>11040</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>4594</td>\n",
       "      <td>175</td>\n",
       "      <td>612</td>\n",
       "      <td>192</td>\n",
       "      <td>705</td>\n",
       "      <td>950</td>\n",
       "      <td>307</td>\n",
       "      <td>17239</td>\n",
       "      <td>14846</td>\n",
       "      <td>...</td>\n",
       "      <td>29577</td>\n",
       "      <td>27588</td>\n",
       "      <td>14077</td>\n",
       "      <td>16752</td>\n",
       "      <td>21303</td>\n",
       "      <td>7542</td>\n",
       "      <td>23354</td>\n",
       "      <td>28496</td>\n",
       "      <td>11572</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>1068</td>\n",
       "      <td>917</td>\n",
       "      <td>606</td>\n",
       "      <td>676</td>\n",
       "      <td>596</td>\n",
       "      <td>34090</td>\n",
       "      <td>17938</td>\n",
       "      <td>14812</td>\n",
       "      <td>28039</td>\n",
       "      <td>...</td>\n",
       "      <td>843</td>\n",
       "      <td>24311</td>\n",
       "      <td>32880</td>\n",
       "      <td>38987</td>\n",
       "      <td>17614</td>\n",
       "      <td>21216</td>\n",
       "      <td>33127</td>\n",
       "      <td>14813</td>\n",
       "      <td>14132</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>1386</td>\n",
       "      <td>818</td>\n",
       "      <td>2135</td>\n",
       "      <td>974</td>\n",
       "      <td>241</td>\n",
       "      <td>1026</td>\n",
       "      <td>1812</td>\n",
       "      <td>688</td>\n",
       "      <td>1343</td>\n",
       "      <td>...</td>\n",
       "      <td>8501</td>\n",
       "      <td>21184</td>\n",
       "      <td>18112</td>\n",
       "      <td>2210</td>\n",
       "      <td>15867</td>\n",
       "      <td>10080</td>\n",
       "      <td>10080</td>\n",
       "      <td>7826</td>\n",
       "      <td>2130</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>2882</td>\n",
       "      <td>871</td>\n",
       "      <td>411</td>\n",
       "      <td>2840</td>\n",
       "      <td>1243</td>\n",
       "      <td>506</td>\n",
       "      <td>1093</td>\n",
       "      <td>11200</td>\n",
       "      <td>21471</td>\n",
       "      <td>...</td>\n",
       "      <td>5771</td>\n",
       "      <td>13326</td>\n",
       "      <td>6142</td>\n",
       "      <td>27368</td>\n",
       "      <td>16076</td>\n",
       "      <td>5530</td>\n",
       "      <td>24348</td>\n",
       "      <td>9677</td>\n",
       "      <td>6113</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>959</td>\n",
       "      <td>328</td>\n",
       "      <td>1629</td>\n",
       "      <td>641</td>\n",
       "      <td>440</td>\n",
       "      <td>548</td>\n",
       "      <td>346</td>\n",
       "      <td>12782</td>\n",
       "      <td>31878</td>\n",
       "      <td>...</td>\n",
       "      <td>24263</td>\n",
       "      <td>57866</td>\n",
       "      <td>33830</td>\n",
       "      <td>67513</td>\n",
       "      <td>35682</td>\n",
       "      <td>27730</td>\n",
       "      <td>45805</td>\n",
       "      <td>18419</td>\n",
       "      <td>750</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>4126</td>\n",
       "      <td>135</td>\n",
       "      <td>258</td>\n",
       "      <td>816</td>\n",
       "      <td>602</td>\n",
       "      <td>465</td>\n",
       "      <td>6962</td>\n",
       "      <td>251</td>\n",
       "      <td>299</td>\n",
       "      <td>...</td>\n",
       "      <td>5904</td>\n",
       "      <td>9638</td>\n",
       "      <td>27994</td>\n",
       "      <td>26993</td>\n",
       "      <td>25477</td>\n",
       "      <td>26392</td>\n",
       "      <td>14783</td>\n",
       "      <td>2233</td>\n",
       "      <td>9466</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>706</td>\n",
       "      <td>2978</td>\n",
       "      <td>662</td>\n",
       "      <td>47</td>\n",
       "      <td>383</td>\n",
       "      <td>643</td>\n",
       "      <td>4018</td>\n",
       "      <td>5668</td>\n",
       "      <td>4839</td>\n",
       "      <td>...</td>\n",
       "      <td>16312</td>\n",
       "      <td>4204</td>\n",
       "      <td>858</td>\n",
       "      <td>15195</td>\n",
       "      <td>20529</td>\n",
       "      <td>17444</td>\n",
       "      <td>17556</td>\n",
       "      <td>15250</td>\n",
       "      <td>12628</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>304</td>\n",
       "      <td>606</td>\n",
       "      <td>316</td>\n",
       "      <td>2275</td>\n",
       "      <td>4103</td>\n",
       "      <td>16187</td>\n",
       "      <td>14692</td>\n",
       "      <td>8681</td>\n",
       "      <td>1295</td>\n",
       "      <td>...</td>\n",
       "      <td>39653</td>\n",
       "      <td>26809</td>\n",
       "      <td>14177</td>\n",
       "      <td>15706</td>\n",
       "      <td>13799</td>\n",
       "      <td>24882</td>\n",
       "      <td>31715</td>\n",
       "      <td>18786</td>\n",
       "      <td>14797</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>112</td>\n",
       "      <td>340</td>\n",
       "      <td>10844</td>\n",
       "      <td>14721</td>\n",
       "      <td>8324</td>\n",
       "      <td>6310</td>\n",
       "      <td>26737</td>\n",
       "      <td>16852</td>\n",
       "      <td>5452</td>\n",
       "      <td>...</td>\n",
       "      <td>2724</td>\n",
       "      <td>1933</td>\n",
       "      <td>118</td>\n",
       "      <td>3679</td>\n",
       "      <td>3587</td>\n",
       "      <td>178</td>\n",
       "      <td>148</td>\n",
       "      <td>2840</td>\n",
       "      <td>0</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>1078</td>\n",
       "      <td>224</td>\n",
       "      <td>1091</td>\n",
       "      <td>209</td>\n",
       "      <td>810</td>\n",
       "      <td>676</td>\n",
       "      <td>1440</td>\n",
       "      <td>43040</td>\n",
       "      <td>26806</td>\n",
       "      <td>...</td>\n",
       "      <td>633</td>\n",
       "      <td>669</td>\n",
       "      <td>23893</td>\n",
       "      <td>5787</td>\n",
       "      <td>5744</td>\n",
       "      <td>2154</td>\n",
       "      <td>8280</td>\n",
       "      <td>8312</td>\n",
       "      <td>5281</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>185</td>\n",
       "      <td>65</td>\n",
       "      <td>233</td>\n",
       "      <td>435</td>\n",
       "      <td>34</td>\n",
       "      <td>110</td>\n",
       "      <td>97</td>\n",
       "      <td>516</td>\n",
       "      <td>17279</td>\n",
       "      <td>...</td>\n",
       "      <td>6152</td>\n",
       "      <td>20672</td>\n",
       "      <td>15809</td>\n",
       "      <td>35751</td>\n",
       "      <td>30866</td>\n",
       "      <td>4359</td>\n",
       "      <td>5973</td>\n",
       "      <td>5071</td>\n",
       "      <td>23938</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>10407</td>\n",
       "      <td>813</td>\n",
       "      <td>383</td>\n",
       "      <td>897</td>\n",
       "      <td>581</td>\n",
       "      <td>314</td>\n",
       "      <td>604</td>\n",
       "      <td>383</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>13615</td>\n",
       "      <td>7349</td>\n",
       "      <td>3011</td>\n",
       "      <td>6775</td>\n",
       "      <td>8720</td>\n",
       "      <td>8566</td>\n",
       "      <td>2726</td>\n",
       "      <td>4785</td>\n",
       "      <td>4848</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>2732</td>\n",
       "      <td>5053</td>\n",
       "      <td>4862</td>\n",
       "      <td>4617</td>\n",
       "      <td>1969</td>\n",
       "      <td>633</td>\n",
       "      <td>2151</td>\n",
       "      <td>1670</td>\n",
       "      <td>2427</td>\n",
       "      <td>...</td>\n",
       "      <td>10505</td>\n",
       "      <td>6546</td>\n",
       "      <td>4641</td>\n",
       "      <td>5641</td>\n",
       "      <td>14100</td>\n",
       "      <td>5129</td>\n",
       "      <td>5050</td>\n",
       "      <td>414</td>\n",
       "      <td>82</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>122</td>\n",
       "      <td>280</td>\n",
       "      <td>399</td>\n",
       "      <td>607</td>\n",
       "      <td>284</td>\n",
       "      <td>580</td>\n",
       "      <td>9617</td>\n",
       "      <td>8456</td>\n",
       "      <td>6791</td>\n",
       "      <td>...</td>\n",
       "      <td>12957</td>\n",
       "      <td>3020</td>\n",
       "      <td>22446</td>\n",
       "      <td>23009</td>\n",
       "      <td>25131</td>\n",
       "      <td>42037</td>\n",
       "      <td>7524</td>\n",
       "      <td>12550</td>\n",
       "      <td>5624</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>163</td>\n",
       "      <td>535</td>\n",
       "      <td>340</td>\n",
       "      <td>518</td>\n",
       "      <td>260</td>\n",
       "      <td>2345</td>\n",
       "      <td>...</td>\n",
       "      <td>2815</td>\n",
       "      <td>10402</td>\n",
       "      <td>6141</td>\n",
       "      <td>7420</td>\n",
       "      <td>25923</td>\n",
       "      <td>1581</td>\n",
       "      <td>11264</td>\n",
       "      <td>5600</td>\n",
       "      <td>1088</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>155</td>\n",
       "      <td>145</td>\n",
       "      <td>354</td>\n",
       "      <td>126</td>\n",
       "      <td>124</td>\n",
       "      <td>120</td>\n",
       "      <td>624</td>\n",
       "      <td>241</td>\n",
       "      <td>804</td>\n",
       "      <td>...</td>\n",
       "      <td>19489</td>\n",
       "      <td>9572</td>\n",
       "      <td>6183</td>\n",
       "      <td>11933</td>\n",
       "      <td>2118</td>\n",
       "      <td>8042</td>\n",
       "      <td>6048</td>\n",
       "      <td>4028</td>\n",
       "      <td>8</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>804</td>\n",
       "      <td>1335</td>\n",
       "      <td>126</td>\n",
       "      <td>4253</td>\n",
       "      <td>1318</td>\n",
       "      <td>926</td>\n",
       "      <td>1901</td>\n",
       "      <td>4419</td>\n",
       "      <td>654</td>\n",
       "      <td>...</td>\n",
       "      <td>27403</td>\n",
       "      <td>13590</td>\n",
       "      <td>23345</td>\n",
       "      <td>6162</td>\n",
       "      <td>23579</td>\n",
       "      <td>16382</td>\n",
       "      <td>6956</td>\n",
       "      <td>5749</td>\n",
       "      <td>389</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>511</td>\n",
       "      <td>2325</td>\n",
       "      <td>580</td>\n",
       "      <td>2808</td>\n",
       "      <td>0</td>\n",
       "      <td>1677</td>\n",
       "      <td>307</td>\n",
       "      <td>3043</td>\n",
       "      <td>1769</td>\n",
       "      <td>...</td>\n",
       "      <td>22059</td>\n",
       "      <td>48563</td>\n",
       "      <td>18268</td>\n",
       "      <td>35373</td>\n",
       "      <td>27431</td>\n",
       "      <td>32513</td>\n",
       "      <td>20643</td>\n",
       "      <td>16746</td>\n",
       "      <td>30018</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 170 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0   0:00  1:00   2:00   3:00  4:00   5:00   6:00   7:00   8:00  \\\n",
       "0            0    480   245    424    242   733     58    600    822   8804   \n",
       "1            0   1532  1535    546    270  5704   9447  28610  19627  24468   \n",
       "2            0   4408  2075    480    480   480    480    480    480    485   \n",
       "3            0   2220   423    203     28   569    388  11980  17591  16399   \n",
       "4            0   4835  3959   6457    807  1710    360    532    544    949   \n",
       "5            0   4594   175    612    192   705    950    307  17239  14846   \n",
       "6            0   1068   917    606    676   596  34090  17938  14812  28039   \n",
       "7            0   1386   818   2135    974   241   1026   1812    688   1343   \n",
       "8            0   2882   871    411   2840  1243    506   1093  11200  21471   \n",
       "9            0    959   328   1629    641   440    548    346  12782  31878   \n",
       "10           0   4126   135    258    816   602    465   6962    251    299   \n",
       "11           0    706  2978    662     47   383    643   4018   5668   4839   \n",
       "12           0    304   606    316   2275  4103  16187  14692   8681   1295   \n",
       "13           0    112   340  10844  14721  8324   6310  26737  16852   5452   \n",
       "14           0   1078   224   1091    209   810    676   1440  43040  26806   \n",
       "15           0    185    65    233    435    34    110     97    516  17279   \n",
       "16           0  10407   813    383    897   581    314    604    383     30   \n",
       "17           0   2732  5053   4862   4617  1969    633   2151   1670   2427   \n",
       "18           0    122   280    399    607   284    580   9617   8456   6791   \n",
       "19           0      0     0     69    163   535    340    518    260   2345   \n",
       "20           0    155   145    354    126   124    120    624    241    804   \n",
       "21           0    804  1335    126   4253  1318    926   1901   4419    654   \n",
       "22           0    511  2325    580   2808     0   1677    307   3043   1769   \n",
       "\n",
       "    ...  15:00.6  16:00.6  17:00.6  18:00.6  19:00.6  20:00.6  21:00.6  \\\n",
       "0   ...    11541    28862    20981    14789    10792     5493    12413   \n",
       "1   ...    31503    18839      628      672      632      356     5879   \n",
       "2   ...    33605    42409    30456    19506    26851    20286    11681   \n",
       "3   ...    35779    24143    52504    44385    43854    30383    26798   \n",
       "4   ...    13525    21183    12676    10663     8813     9488     5794   \n",
       "5   ...    29577    27588    14077    16752    21303     7542    23354   \n",
       "6   ...      843    24311    32880    38987    17614    21216    33127   \n",
       "7   ...     8501    21184    18112     2210    15867    10080    10080   \n",
       "8   ...     5771    13326     6142    27368    16076     5530    24348   \n",
       "9   ...    24263    57866    33830    67513    35682    27730    45805   \n",
       "10  ...     5904     9638    27994    26993    25477    26392    14783   \n",
       "11  ...    16312     4204      858    15195    20529    17444    17556   \n",
       "12  ...    39653    26809    14177    15706    13799    24882    31715   \n",
       "13  ...     2724     1933      118     3679     3587      178      148   \n",
       "14  ...      633      669    23893     5787     5744     2154     8280   \n",
       "15  ...     6152    20672    15809    35751    30866     4359     5973   \n",
       "16  ...    13615     7349     3011     6775     8720     8566     2726   \n",
       "17  ...    10505     6546     4641     5641    14100     5129     5050   \n",
       "18  ...    12957     3020    22446    23009    25131    42037     7524   \n",
       "19  ...     2815    10402     6141     7420    25923     1581    11264   \n",
       "20  ...    19489     9572     6183    11933     2118     8042     6048   \n",
       "21  ...    27403    13590    23345     6162    23579    16382     6956   \n",
       "22  ...    22059    48563    18268    35373    27431    32513    20643   \n",
       "\n",
       "    22:00.6  23:00.6         Id  \n",
       "0     11248     4485  condition  \n",
       "1      2537     1537  condition  \n",
       "2      2561    19681  condition  \n",
       "3      4657     8929  condition  \n",
       "4      3055    11040  condition  \n",
       "5     28496    11572  condition  \n",
       "6     14813    14132  condition  \n",
       "7      7826     2130  condition  \n",
       "8      9677     6113  condition  \n",
       "9     18419      750  condition  \n",
       "10     2233     9466  condition  \n",
       "11    15250    12628  condition  \n",
       "12    18786    14797  condition  \n",
       "13     2840        0  condition  \n",
       "14     8312     5281  condition  \n",
       "15     5071    23938  condition  \n",
       "16     4785     4848  condition  \n",
       "17      414       82  condition  \n",
       "18    12550     5624  condition  \n",
       "19     5600     1088  condition  \n",
       "20     4028        8  condition  \n",
       "21     5749      389  condition  \n",
       "22    16746    30018  condition  \n",
       "\n",
       "[23 rows x 170 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df.drop(['Unnamed: 0'], axis=1, inplace= True)\n",
    "my_df.isnull().values.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0:00</th>\n",
       "      <th>1:00</th>\n",
       "      <th>2:00</th>\n",
       "      <th>3:00</th>\n",
       "      <th>4:00</th>\n",
       "      <th>5:00</th>\n",
       "      <th>6:00</th>\n",
       "      <th>7:00</th>\n",
       "      <th>8:00</th>\n",
       "      <th>9:00</th>\n",
       "      <th>...</th>\n",
       "      <th>15:00.6</th>\n",
       "      <th>16:00.6</th>\n",
       "      <th>17:00.6</th>\n",
       "      <th>18:00.6</th>\n",
       "      <th>19:00.6</th>\n",
       "      <th>20:00.6</th>\n",
       "      <th>21:00.6</th>\n",
       "      <th>22:00.6</th>\n",
       "      <th>23:00.6</th>\n",
       "      <th>Id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>480</td>\n",
       "      <td>245</td>\n",
       "      <td>424</td>\n",
       "      <td>242</td>\n",
       "      <td>733</td>\n",
       "      <td>58</td>\n",
       "      <td>600</td>\n",
       "      <td>822</td>\n",
       "      <td>8804</td>\n",
       "      <td>6687</td>\n",
       "      <td>...</td>\n",
       "      <td>11541</td>\n",
       "      <td>28862</td>\n",
       "      <td>20981</td>\n",
       "      <td>14789</td>\n",
       "      <td>10792</td>\n",
       "      <td>5493</td>\n",
       "      <td>12413</td>\n",
       "      <td>11248</td>\n",
       "      <td>4485</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1532</td>\n",
       "      <td>1535</td>\n",
       "      <td>546</td>\n",
       "      <td>270</td>\n",
       "      <td>5704</td>\n",
       "      <td>9447</td>\n",
       "      <td>28610</td>\n",
       "      <td>19627</td>\n",
       "      <td>24468</td>\n",
       "      <td>30029</td>\n",
       "      <td>...</td>\n",
       "      <td>31503</td>\n",
       "      <td>18839</td>\n",
       "      <td>628</td>\n",
       "      <td>672</td>\n",
       "      <td>632</td>\n",
       "      <td>356</td>\n",
       "      <td>5879</td>\n",
       "      <td>2537</td>\n",
       "      <td>1537</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4408</td>\n",
       "      <td>2075</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>485</td>\n",
       "      <td>19090</td>\n",
       "      <td>...</td>\n",
       "      <td>33605</td>\n",
       "      <td>42409</td>\n",
       "      <td>30456</td>\n",
       "      <td>19506</td>\n",
       "      <td>26851</td>\n",
       "      <td>20286</td>\n",
       "      <td>11681</td>\n",
       "      <td>2561</td>\n",
       "      <td>19681</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2220</td>\n",
       "      <td>423</td>\n",
       "      <td>203</td>\n",
       "      <td>28</td>\n",
       "      <td>569</td>\n",
       "      <td>388</td>\n",
       "      <td>11980</td>\n",
       "      <td>17591</td>\n",
       "      <td>16399</td>\n",
       "      <td>22316</td>\n",
       "      <td>...</td>\n",
       "      <td>35779</td>\n",
       "      <td>24143</td>\n",
       "      <td>52504</td>\n",
       "      <td>44385</td>\n",
       "      <td>43854</td>\n",
       "      <td>30383</td>\n",
       "      <td>26798</td>\n",
       "      <td>4657</td>\n",
       "      <td>8929</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4835</td>\n",
       "      <td>3959</td>\n",
       "      <td>6457</td>\n",
       "      <td>807</td>\n",
       "      <td>1710</td>\n",
       "      <td>360</td>\n",
       "      <td>532</td>\n",
       "      <td>544</td>\n",
       "      <td>949</td>\n",
       "      <td>9951</td>\n",
       "      <td>...</td>\n",
       "      <td>13525</td>\n",
       "      <td>21183</td>\n",
       "      <td>12676</td>\n",
       "      <td>10663</td>\n",
       "      <td>8813</td>\n",
       "      <td>9488</td>\n",
       "      <td>5794</td>\n",
       "      <td>3055</td>\n",
       "      <td>11040</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4594</td>\n",
       "      <td>175</td>\n",
       "      <td>612</td>\n",
       "      <td>192</td>\n",
       "      <td>705</td>\n",
       "      <td>950</td>\n",
       "      <td>307</td>\n",
       "      <td>17239</td>\n",
       "      <td>14846</td>\n",
       "      <td>6839</td>\n",
       "      <td>...</td>\n",
       "      <td>29577</td>\n",
       "      <td>27588</td>\n",
       "      <td>14077</td>\n",
       "      <td>16752</td>\n",
       "      <td>21303</td>\n",
       "      <td>7542</td>\n",
       "      <td>23354</td>\n",
       "      <td>28496</td>\n",
       "      <td>11572</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1068</td>\n",
       "      <td>917</td>\n",
       "      <td>606</td>\n",
       "      <td>676</td>\n",
       "      <td>596</td>\n",
       "      <td>34090</td>\n",
       "      <td>17938</td>\n",
       "      <td>14812</td>\n",
       "      <td>28039</td>\n",
       "      <td>33920</td>\n",
       "      <td>...</td>\n",
       "      <td>843</td>\n",
       "      <td>24311</td>\n",
       "      <td>32880</td>\n",
       "      <td>38987</td>\n",
       "      <td>17614</td>\n",
       "      <td>21216</td>\n",
       "      <td>33127</td>\n",
       "      <td>14813</td>\n",
       "      <td>14132</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1386</td>\n",
       "      <td>818</td>\n",
       "      <td>2135</td>\n",
       "      <td>974</td>\n",
       "      <td>241</td>\n",
       "      <td>1026</td>\n",
       "      <td>1812</td>\n",
       "      <td>688</td>\n",
       "      <td>1343</td>\n",
       "      <td>3193</td>\n",
       "      <td>...</td>\n",
       "      <td>8501</td>\n",
       "      <td>21184</td>\n",
       "      <td>18112</td>\n",
       "      <td>2210</td>\n",
       "      <td>15867</td>\n",
       "      <td>10080</td>\n",
       "      <td>10080</td>\n",
       "      <td>7826</td>\n",
       "      <td>2130</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2882</td>\n",
       "      <td>871</td>\n",
       "      <td>411</td>\n",
       "      <td>2840</td>\n",
       "      <td>1243</td>\n",
       "      <td>506</td>\n",
       "      <td>1093</td>\n",
       "      <td>11200</td>\n",
       "      <td>21471</td>\n",
       "      <td>25424</td>\n",
       "      <td>...</td>\n",
       "      <td>5771</td>\n",
       "      <td>13326</td>\n",
       "      <td>6142</td>\n",
       "      <td>27368</td>\n",
       "      <td>16076</td>\n",
       "      <td>5530</td>\n",
       "      <td>24348</td>\n",
       "      <td>9677</td>\n",
       "      <td>6113</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>959</td>\n",
       "      <td>328</td>\n",
       "      <td>1629</td>\n",
       "      <td>641</td>\n",
       "      <td>440</td>\n",
       "      <td>548</td>\n",
       "      <td>346</td>\n",
       "      <td>12782</td>\n",
       "      <td>31878</td>\n",
       "      <td>24143</td>\n",
       "      <td>...</td>\n",
       "      <td>24263</td>\n",
       "      <td>57866</td>\n",
       "      <td>33830</td>\n",
       "      <td>67513</td>\n",
       "      <td>35682</td>\n",
       "      <td>27730</td>\n",
       "      <td>45805</td>\n",
       "      <td>18419</td>\n",
       "      <td>750</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4126</td>\n",
       "      <td>135</td>\n",
       "      <td>258</td>\n",
       "      <td>816</td>\n",
       "      <td>602</td>\n",
       "      <td>465</td>\n",
       "      <td>6962</td>\n",
       "      <td>251</td>\n",
       "      <td>299</td>\n",
       "      <td>2538</td>\n",
       "      <td>...</td>\n",
       "      <td>5904</td>\n",
       "      <td>9638</td>\n",
       "      <td>27994</td>\n",
       "      <td>26993</td>\n",
       "      <td>25477</td>\n",
       "      <td>26392</td>\n",
       "      <td>14783</td>\n",
       "      <td>2233</td>\n",
       "      <td>9466</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>706</td>\n",
       "      <td>2978</td>\n",
       "      <td>662</td>\n",
       "      <td>47</td>\n",
       "      <td>383</td>\n",
       "      <td>643</td>\n",
       "      <td>4018</td>\n",
       "      <td>5668</td>\n",
       "      <td>4839</td>\n",
       "      <td>3091</td>\n",
       "      <td>...</td>\n",
       "      <td>16312</td>\n",
       "      <td>4204</td>\n",
       "      <td>858</td>\n",
       "      <td>15195</td>\n",
       "      <td>20529</td>\n",
       "      <td>17444</td>\n",
       "      <td>17556</td>\n",
       "      <td>15250</td>\n",
       "      <td>12628</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>304</td>\n",
       "      <td>606</td>\n",
       "      <td>316</td>\n",
       "      <td>2275</td>\n",
       "      <td>4103</td>\n",
       "      <td>16187</td>\n",
       "      <td>14692</td>\n",
       "      <td>8681</td>\n",
       "      <td>1295</td>\n",
       "      <td>1176</td>\n",
       "      <td>...</td>\n",
       "      <td>39653</td>\n",
       "      <td>26809</td>\n",
       "      <td>14177</td>\n",
       "      <td>15706</td>\n",
       "      <td>13799</td>\n",
       "      <td>24882</td>\n",
       "      <td>31715</td>\n",
       "      <td>18786</td>\n",
       "      <td>14797</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>112</td>\n",
       "      <td>340</td>\n",
       "      <td>10844</td>\n",
       "      <td>14721</td>\n",
       "      <td>8324</td>\n",
       "      <td>6310</td>\n",
       "      <td>26737</td>\n",
       "      <td>16852</td>\n",
       "      <td>5452</td>\n",
       "      <td>589</td>\n",
       "      <td>...</td>\n",
       "      <td>2724</td>\n",
       "      <td>1933</td>\n",
       "      <td>118</td>\n",
       "      <td>3679</td>\n",
       "      <td>3587</td>\n",
       "      <td>178</td>\n",
       "      <td>148</td>\n",
       "      <td>2840</td>\n",
       "      <td>0</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1078</td>\n",
       "      <td>224</td>\n",
       "      <td>1091</td>\n",
       "      <td>209</td>\n",
       "      <td>810</td>\n",
       "      <td>676</td>\n",
       "      <td>1440</td>\n",
       "      <td>43040</td>\n",
       "      <td>26806</td>\n",
       "      <td>12270</td>\n",
       "      <td>...</td>\n",
       "      <td>633</td>\n",
       "      <td>669</td>\n",
       "      <td>23893</td>\n",
       "      <td>5787</td>\n",
       "      <td>5744</td>\n",
       "      <td>2154</td>\n",
       "      <td>8280</td>\n",
       "      <td>8312</td>\n",
       "      <td>5281</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>185</td>\n",
       "      <td>65</td>\n",
       "      <td>233</td>\n",
       "      <td>435</td>\n",
       "      <td>34</td>\n",
       "      <td>110</td>\n",
       "      <td>97</td>\n",
       "      <td>516</td>\n",
       "      <td>17279</td>\n",
       "      <td>6196</td>\n",
       "      <td>...</td>\n",
       "      <td>6152</td>\n",
       "      <td>20672</td>\n",
       "      <td>15809</td>\n",
       "      <td>35751</td>\n",
       "      <td>30866</td>\n",
       "      <td>4359</td>\n",
       "      <td>5973</td>\n",
       "      <td>5071</td>\n",
       "      <td>23938</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10407</td>\n",
       "      <td>813</td>\n",
       "      <td>383</td>\n",
       "      <td>897</td>\n",
       "      <td>581</td>\n",
       "      <td>314</td>\n",
       "      <td>604</td>\n",
       "      <td>383</td>\n",
       "      <td>30</td>\n",
       "      <td>1682</td>\n",
       "      <td>...</td>\n",
       "      <td>13615</td>\n",
       "      <td>7349</td>\n",
       "      <td>3011</td>\n",
       "      <td>6775</td>\n",
       "      <td>8720</td>\n",
       "      <td>8566</td>\n",
       "      <td>2726</td>\n",
       "      <td>4785</td>\n",
       "      <td>4848</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2732</td>\n",
       "      <td>5053</td>\n",
       "      <td>4862</td>\n",
       "      <td>4617</td>\n",
       "      <td>1969</td>\n",
       "      <td>633</td>\n",
       "      <td>2151</td>\n",
       "      <td>1670</td>\n",
       "      <td>2427</td>\n",
       "      <td>2457</td>\n",
       "      <td>...</td>\n",
       "      <td>10505</td>\n",
       "      <td>6546</td>\n",
       "      <td>4641</td>\n",
       "      <td>5641</td>\n",
       "      <td>14100</td>\n",
       "      <td>5129</td>\n",
       "      <td>5050</td>\n",
       "      <td>414</td>\n",
       "      <td>82</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>122</td>\n",
       "      <td>280</td>\n",
       "      <td>399</td>\n",
       "      <td>607</td>\n",
       "      <td>284</td>\n",
       "      <td>580</td>\n",
       "      <td>9617</td>\n",
       "      <td>8456</td>\n",
       "      <td>6791</td>\n",
       "      <td>6327</td>\n",
       "      <td>...</td>\n",
       "      <td>12957</td>\n",
       "      <td>3020</td>\n",
       "      <td>22446</td>\n",
       "      <td>23009</td>\n",
       "      <td>25131</td>\n",
       "      <td>42037</td>\n",
       "      <td>7524</td>\n",
       "      <td>12550</td>\n",
       "      <td>5624</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>163</td>\n",
       "      <td>535</td>\n",
       "      <td>340</td>\n",
       "      <td>518</td>\n",
       "      <td>260</td>\n",
       "      <td>2345</td>\n",
       "      <td>6019</td>\n",
       "      <td>...</td>\n",
       "      <td>2815</td>\n",
       "      <td>10402</td>\n",
       "      <td>6141</td>\n",
       "      <td>7420</td>\n",
       "      <td>25923</td>\n",
       "      <td>1581</td>\n",
       "      <td>11264</td>\n",
       "      <td>5600</td>\n",
       "      <td>1088</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>155</td>\n",
       "      <td>145</td>\n",
       "      <td>354</td>\n",
       "      <td>126</td>\n",
       "      <td>124</td>\n",
       "      <td>120</td>\n",
       "      <td>624</td>\n",
       "      <td>241</td>\n",
       "      <td>804</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>19489</td>\n",
       "      <td>9572</td>\n",
       "      <td>6183</td>\n",
       "      <td>11933</td>\n",
       "      <td>2118</td>\n",
       "      <td>8042</td>\n",
       "      <td>6048</td>\n",
       "      <td>4028</td>\n",
       "      <td>8</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>804</td>\n",
       "      <td>1335</td>\n",
       "      <td>126</td>\n",
       "      <td>4253</td>\n",
       "      <td>1318</td>\n",
       "      <td>926</td>\n",
       "      <td>1901</td>\n",
       "      <td>4419</td>\n",
       "      <td>654</td>\n",
       "      <td>210</td>\n",
       "      <td>...</td>\n",
       "      <td>27403</td>\n",
       "      <td>13590</td>\n",
       "      <td>23345</td>\n",
       "      <td>6162</td>\n",
       "      <td>23579</td>\n",
       "      <td>16382</td>\n",
       "      <td>6956</td>\n",
       "      <td>5749</td>\n",
       "      <td>389</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>511</td>\n",
       "      <td>2325</td>\n",
       "      <td>580</td>\n",
       "      <td>2808</td>\n",
       "      <td>0</td>\n",
       "      <td>1677</td>\n",
       "      <td>307</td>\n",
       "      <td>3043</td>\n",
       "      <td>1769</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>22059</td>\n",
       "      <td>48563</td>\n",
       "      <td>18268</td>\n",
       "      <td>35373</td>\n",
       "      <td>27431</td>\n",
       "      <td>32513</td>\n",
       "      <td>20643</td>\n",
       "      <td>16746</td>\n",
       "      <td>30018</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 169 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0:00  1:00   2:00   3:00  4:00   5:00   6:00   7:00   8:00   9:00  ...  \\\n",
       "0     480   245    424    242   733     58    600    822   8804   6687  ...   \n",
       "1    1532  1535    546    270  5704   9447  28610  19627  24468  30029  ...   \n",
       "2    4408  2075    480    480   480    480    480    480    485  19090  ...   \n",
       "3    2220   423    203     28   569    388  11980  17591  16399  22316  ...   \n",
       "4    4835  3959   6457    807  1710    360    532    544    949   9951  ...   \n",
       "5    4594   175    612    192   705    950    307  17239  14846   6839  ...   \n",
       "6    1068   917    606    676   596  34090  17938  14812  28039  33920  ...   \n",
       "7    1386   818   2135    974   241   1026   1812    688   1343   3193  ...   \n",
       "8    2882   871    411   2840  1243    506   1093  11200  21471  25424  ...   \n",
       "9     959   328   1629    641   440    548    346  12782  31878  24143  ...   \n",
       "10   4126   135    258    816   602    465   6962    251    299   2538  ...   \n",
       "11    706  2978    662     47   383    643   4018   5668   4839   3091  ...   \n",
       "12    304   606    316   2275  4103  16187  14692   8681   1295   1176  ...   \n",
       "13    112   340  10844  14721  8324   6310  26737  16852   5452    589  ...   \n",
       "14   1078   224   1091    209   810    676   1440  43040  26806  12270  ...   \n",
       "15    185    65    233    435    34    110     97    516  17279   6196  ...   \n",
       "16  10407   813    383    897   581    314    604    383     30   1682  ...   \n",
       "17   2732  5053   4862   4617  1969    633   2151   1670   2427   2457  ...   \n",
       "18    122   280    399    607   284    580   9617   8456   6791   6327  ...   \n",
       "19      0     0     69    163   535    340    518    260   2345   6019  ...   \n",
       "20    155   145    354    126   124    120    624    241    804     13  ...   \n",
       "21    804  1335    126   4253  1318    926   1901   4419    654    210  ...   \n",
       "22    511  2325    580   2808     0   1677    307   3043   1769   2015  ...   \n",
       "\n",
       "    15:00.6  16:00.6  17:00.6  18:00.6  19:00.6  20:00.6  21:00.6  22:00.6  \\\n",
       "0     11541    28862    20981    14789    10792     5493    12413    11248   \n",
       "1     31503    18839      628      672      632      356     5879     2537   \n",
       "2     33605    42409    30456    19506    26851    20286    11681     2561   \n",
       "3     35779    24143    52504    44385    43854    30383    26798     4657   \n",
       "4     13525    21183    12676    10663     8813     9488     5794     3055   \n",
       "5     29577    27588    14077    16752    21303     7542    23354    28496   \n",
       "6       843    24311    32880    38987    17614    21216    33127    14813   \n",
       "7      8501    21184    18112     2210    15867    10080    10080     7826   \n",
       "8      5771    13326     6142    27368    16076     5530    24348     9677   \n",
       "9     24263    57866    33830    67513    35682    27730    45805    18419   \n",
       "10     5904     9638    27994    26993    25477    26392    14783     2233   \n",
       "11    16312     4204      858    15195    20529    17444    17556    15250   \n",
       "12    39653    26809    14177    15706    13799    24882    31715    18786   \n",
       "13     2724     1933      118     3679     3587      178      148     2840   \n",
       "14      633      669    23893     5787     5744     2154     8280     8312   \n",
       "15     6152    20672    15809    35751    30866     4359     5973     5071   \n",
       "16    13615     7349     3011     6775     8720     8566     2726     4785   \n",
       "17    10505     6546     4641     5641    14100     5129     5050      414   \n",
       "18    12957     3020    22446    23009    25131    42037     7524    12550   \n",
       "19     2815    10402     6141     7420    25923     1581    11264     5600   \n",
       "20    19489     9572     6183    11933     2118     8042     6048     4028   \n",
       "21    27403    13590    23345     6162    23579    16382     6956     5749   \n",
       "22    22059    48563    18268    35373    27431    32513    20643    16746   \n",
       "\n",
       "    23:00.6         Id  \n",
       "0      4485  condition  \n",
       "1      1537  condition  \n",
       "2     19681  condition  \n",
       "3      8929  condition  \n",
       "4     11040  condition  \n",
       "5     11572  condition  \n",
       "6     14132  condition  \n",
       "7      2130  condition  \n",
       "8      6113  condition  \n",
       "9       750  condition  \n",
       "10     9466  condition  \n",
       "11    12628  condition  \n",
       "12    14797  condition  \n",
       "13        0  condition  \n",
       "14     5281  condition  \n",
       "15    23938  condition  \n",
       "16     4848  condition  \n",
       "17       82  condition  \n",
       "18     5624  condition  \n",
       "19     1088  condition  \n",
       "20        8  condition  \n",
       "21      389  condition  \n",
       "22    30018  condition  \n",
       "\n",
       "[23 rows x 169 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "week_columns = my_df.drop(['Id'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0:00</th>\n",
       "      <th>1:00</th>\n",
       "      <th>2:00</th>\n",
       "      <th>3:00</th>\n",
       "      <th>4:00</th>\n",
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       "      <th>7:00</th>\n",
       "      <th>8:00</th>\n",
       "      <th>9:00</th>\n",
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       "      <th>20:00.6</th>\n",
       "      <th>21:00.6</th>\n",
       "      <th>22:00.6</th>\n",
       "      <th>23:00.6</th>\n",
       "      <th>Id</th>\n",
       "      <th>Max</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>SD</th>\n",
       "      <th>Var</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>480</td>\n",
       "      <td>245</td>\n",
       "      <td>424</td>\n",
       "      <td>242</td>\n",
       "      <td>733</td>\n",
       "      <td>58</td>\n",
       "      <td>600</td>\n",
       "      <td>822</td>\n",
       "      <td>8804</td>\n",
       "      <td>6687</td>\n",
       "      <td>...</td>\n",
       "      <td>5493</td>\n",
       "      <td>12413</td>\n",
       "      <td>11248</td>\n",
       "      <td>4485</td>\n",
       "      <td>condition</td>\n",
       "      <td>68238</td>\n",
       "      <td>9392.732143</td>\n",
       "      <td>6033.0</td>\n",
       "      <td>11629.952868</td>\n",
       "      <td>1.352558e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1532</td>\n",
       "      <td>1535</td>\n",
       "      <td>546</td>\n",
       "      <td>270</td>\n",
       "      <td>5704</td>\n",
       "      <td>9447</td>\n",
       "      <td>28610</td>\n",
       "      <td>19627</td>\n",
       "      <td>24468</td>\n",
       "      <td>30029</td>\n",
       "      <td>...</td>\n",
       "      <td>356</td>\n",
       "      <td>5879</td>\n",
       "      <td>2537</td>\n",
       "      <td>1537</td>\n",
       "      <td>condition</td>\n",
       "      <td>64882</td>\n",
       "      <td>12579.583333</td>\n",
       "      <td>7622.5</td>\n",
       "      <td>13651.806945</td>\n",
       "      <td>1.863718e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4408</td>\n",
       "      <td>2075</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>485</td>\n",
       "      <td>19090</td>\n",
       "      <td>...</td>\n",
       "      <td>20286</td>\n",
       "      <td>11681</td>\n",
       "      <td>2561</td>\n",
       "      <td>19681</td>\n",
       "      <td>condition</td>\n",
       "      <td>68830</td>\n",
       "      <td>15732.833333</td>\n",
       "      <td>14450.5</td>\n",
       "      <td>14848.824389</td>\n",
       "      <td>2.204876e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2220</td>\n",
       "      <td>423</td>\n",
       "      <td>203</td>\n",
       "      <td>28</td>\n",
       "      <td>569</td>\n",
       "      <td>388</td>\n",
       "      <td>11980</td>\n",
       "      <td>17591</td>\n",
       "      <td>16399</td>\n",
       "      <td>22316</td>\n",
       "      <td>...</td>\n",
       "      <td>30383</td>\n",
       "      <td>26798</td>\n",
       "      <td>4657</td>\n",
       "      <td>8929</td>\n",
       "      <td>condition</td>\n",
       "      <td>64887</td>\n",
       "      <td>12277.755952</td>\n",
       "      <td>10132.0</td>\n",
       "      <td>11670.505975</td>\n",
       "      <td>1.362007e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4835</td>\n",
       "      <td>3959</td>\n",
       "      <td>6457</td>\n",
       "      <td>807</td>\n",
       "      <td>1710</td>\n",
       "      <td>360</td>\n",
       "      <td>532</td>\n",
       "      <td>544</td>\n",
       "      <td>949</td>\n",
       "      <td>9951</td>\n",
       "      <td>...</td>\n",
       "      <td>9488</td>\n",
       "      <td>5794</td>\n",
       "      <td>3055</td>\n",
       "      <td>11040</td>\n",
       "      <td>condition</td>\n",
       "      <td>62282</td>\n",
       "      <td>9496.154762</td>\n",
       "      <td>7076.0</td>\n",
       "      <td>9659.991062</td>\n",
       "      <td>9.331543e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4594</td>\n",
       "      <td>175</td>\n",
       "      <td>612</td>\n",
       "      <td>192</td>\n",
       "      <td>705</td>\n",
       "      <td>950</td>\n",
       "      <td>307</td>\n",
       "      <td>17239</td>\n",
       "      <td>14846</td>\n",
       "      <td>6839</td>\n",
       "      <td>...</td>\n",
       "      <td>7542</td>\n",
       "      <td>23354</td>\n",
       "      <td>28496</td>\n",
       "      <td>11572</td>\n",
       "      <td>condition</td>\n",
       "      <td>56630</td>\n",
       "      <td>11060.553571</td>\n",
       "      <td>8384.5</td>\n",
       "      <td>11243.680391</td>\n",
       "      <td>1.264203e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1068</td>\n",
       "      <td>917</td>\n",
       "      <td>606</td>\n",
       "      <td>676</td>\n",
       "      <td>596</td>\n",
       "      <td>34090</td>\n",
       "      <td>17938</td>\n",
       "      <td>14812</td>\n",
       "      <td>28039</td>\n",
       "      <td>33920</td>\n",
       "      <td>...</td>\n",
       "      <td>21216</td>\n",
       "      <td>33127</td>\n",
       "      <td>14813</td>\n",
       "      <td>14132</td>\n",
       "      <td>condition</td>\n",
       "      <td>75525</td>\n",
       "      <td>17277.238095</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>20781.392660</td>\n",
       "      <td>4.318663e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1386</td>\n",
       "      <td>818</td>\n",
       "      <td>2135</td>\n",
       "      <td>974</td>\n",
       "      <td>241</td>\n",
       "      <td>1026</td>\n",
       "      <td>1812</td>\n",
       "      <td>688</td>\n",
       "      <td>1343</td>\n",
       "      <td>3193</td>\n",
       "      <td>...</td>\n",
       "      <td>10080</td>\n",
       "      <td>10080</td>\n",
       "      <td>7826</td>\n",
       "      <td>2130</td>\n",
       "      <td>condition</td>\n",
       "      <td>130377</td>\n",
       "      <td>13690.857143</td>\n",
       "      <td>6695.0</td>\n",
       "      <td>17782.014525</td>\n",
       "      <td>3.162000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2882</td>\n",
       "      <td>871</td>\n",
       "      <td>411</td>\n",
       "      <td>2840</td>\n",
       "      <td>1243</td>\n",
       "      <td>506</td>\n",
       "      <td>1093</td>\n",
       "      <td>11200</td>\n",
       "      <td>21471</td>\n",
       "      <td>25424</td>\n",
       "      <td>...</td>\n",
       "      <td>5530</td>\n",
       "      <td>24348</td>\n",
       "      <td>9677</td>\n",
       "      <td>6113</td>\n",
       "      <td>condition</td>\n",
       "      <td>47419</td>\n",
       "      <td>10508.839286</td>\n",
       "      <td>9114.5</td>\n",
       "      <td>9566.698553</td>\n",
       "      <td>9.152172e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>959</td>\n",
       "      <td>328</td>\n",
       "      <td>1629</td>\n",
       "      <td>641</td>\n",
       "      <td>440</td>\n",
       "      <td>548</td>\n",
       "      <td>346</td>\n",
       "      <td>12782</td>\n",
       "      <td>31878</td>\n",
       "      <td>24143</td>\n",
       "      <td>...</td>\n",
       "      <td>27730</td>\n",
       "      <td>45805</td>\n",
       "      <td>18419</td>\n",
       "      <td>750</td>\n",
       "      <td>condition</td>\n",
       "      <td>67513</td>\n",
       "      <td>20614.577381</td>\n",
       "      <td>19825.0</td>\n",
       "      <td>17386.567358</td>\n",
       "      <td>3.022927e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4126</td>\n",
       "      <td>135</td>\n",
       "      <td>258</td>\n",
       "      <td>816</td>\n",
       "      <td>602</td>\n",
       "      <td>465</td>\n",
       "      <td>6962</td>\n",
       "      <td>251</td>\n",
       "      <td>299</td>\n",
       "      <td>2538</td>\n",
       "      <td>...</td>\n",
       "      <td>26392</td>\n",
       "      <td>14783</td>\n",
       "      <td>2233</td>\n",
       "      <td>9466</td>\n",
       "      <td>condition</td>\n",
       "      <td>42125</td>\n",
       "      <td>7661.291667</td>\n",
       "      <td>3622.5</td>\n",
       "      <td>9019.642224</td>\n",
       "      <td>8.135395e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>706</td>\n",
       "      <td>2978</td>\n",
       "      <td>662</td>\n",
       "      <td>47</td>\n",
       "      <td>383</td>\n",
       "      <td>643</td>\n",
       "      <td>4018</td>\n",
       "      <td>5668</td>\n",
       "      <td>4839</td>\n",
       "      <td>3091</td>\n",
       "      <td>...</td>\n",
       "      <td>17444</td>\n",
       "      <td>17556</td>\n",
       "      <td>15250</td>\n",
       "      <td>12628</td>\n",
       "      <td>condition</td>\n",
       "      <td>63559</td>\n",
       "      <td>11032.392857</td>\n",
       "      <td>8327.5</td>\n",
       "      <td>10556.284190</td>\n",
       "      <td>1.114351e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>304</td>\n",
       "      <td>606</td>\n",
       "      <td>316</td>\n",
       "      <td>2275</td>\n",
       "      <td>4103</td>\n",
       "      <td>16187</td>\n",
       "      <td>14692</td>\n",
       "      <td>8681</td>\n",
       "      <td>1295</td>\n",
       "      <td>1176</td>\n",
       "      <td>...</td>\n",
       "      <td>24882</td>\n",
       "      <td>31715</td>\n",
       "      <td>18786</td>\n",
       "      <td>14797</td>\n",
       "      <td>condition</td>\n",
       "      <td>54389</td>\n",
       "      <td>15232.261905</td>\n",
       "      <td>14204.0</td>\n",
       "      <td>12482.881080</td>\n",
       "      <td>1.558223e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>112</td>\n",
       "      <td>340</td>\n",
       "      <td>10844</td>\n",
       "      <td>14721</td>\n",
       "      <td>8324</td>\n",
       "      <td>6310</td>\n",
       "      <td>26737</td>\n",
       "      <td>16852</td>\n",
       "      <td>5452</td>\n",
       "      <td>589</td>\n",
       "      <td>...</td>\n",
       "      <td>178</td>\n",
       "      <td>148</td>\n",
       "      <td>2840</td>\n",
       "      <td>0</td>\n",
       "      <td>condition</td>\n",
       "      <td>44674</td>\n",
       "      <td>4643.047619</td>\n",
       "      <td>2959.0</td>\n",
       "      <td>5865.685480</td>\n",
       "      <td>3.440627e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1078</td>\n",
       "      <td>224</td>\n",
       "      <td>1091</td>\n",
       "      <td>209</td>\n",
       "      <td>810</td>\n",
       "      <td>676</td>\n",
       "      <td>1440</td>\n",
       "      <td>43040</td>\n",
       "      <td>26806</td>\n",
       "      <td>12270</td>\n",
       "      <td>...</td>\n",
       "      <td>2154</td>\n",
       "      <td>8280</td>\n",
       "      <td>8312</td>\n",
       "      <td>5281</td>\n",
       "      <td>condition</td>\n",
       "      <td>65955</td>\n",
       "      <td>6912.255952</td>\n",
       "      <td>4030.5</td>\n",
       "      <td>9108.537166</td>\n",
       "      <td>8.296545e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>185</td>\n",
       "      <td>65</td>\n",
       "      <td>233</td>\n",
       "      <td>435</td>\n",
       "      <td>34</td>\n",
       "      <td>110</td>\n",
       "      <td>97</td>\n",
       "      <td>516</td>\n",
       "      <td>17279</td>\n",
       "      <td>6196</td>\n",
       "      <td>...</td>\n",
       "      <td>4359</td>\n",
       "      <td>5973</td>\n",
       "      <td>5071</td>\n",
       "      <td>23938</td>\n",
       "      <td>condition</td>\n",
       "      <td>90108</td>\n",
       "      <td>16461.041667</td>\n",
       "      <td>12019.0</td>\n",
       "      <td>17145.700575</td>\n",
       "      <td>2.939750e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10407</td>\n",
       "      <td>813</td>\n",
       "      <td>383</td>\n",
       "      <td>897</td>\n",
       "      <td>581</td>\n",
       "      <td>314</td>\n",
       "      <td>604</td>\n",
       "      <td>383</td>\n",
       "      <td>30</td>\n",
       "      <td>1682</td>\n",
       "      <td>...</td>\n",
       "      <td>8566</td>\n",
       "      <td>2726</td>\n",
       "      <td>4785</td>\n",
       "      <td>4848</td>\n",
       "      <td>condition</td>\n",
       "      <td>16283</td>\n",
       "      <td>4815.428571</td>\n",
       "      <td>4088.0</td>\n",
       "      <td>4010.180922</td>\n",
       "      <td>1.608155e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2732</td>\n",
       "      <td>5053</td>\n",
       "      <td>4862</td>\n",
       "      <td>4617</td>\n",
       "      <td>1969</td>\n",
       "      <td>633</td>\n",
       "      <td>2151</td>\n",
       "      <td>1670</td>\n",
       "      <td>2427</td>\n",
       "      <td>2457</td>\n",
       "      <td>...</td>\n",
       "      <td>5129</td>\n",
       "      <td>5050</td>\n",
       "      <td>414</td>\n",
       "      <td>82</td>\n",
       "      <td>condition</td>\n",
       "      <td>16569</td>\n",
       "      <td>4232.446429</td>\n",
       "      <td>4167.5</td>\n",
       "      <td>3055.384235</td>\n",
       "      <td>9.335373e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>122</td>\n",
       "      <td>280</td>\n",
       "      <td>399</td>\n",
       "      <td>607</td>\n",
       "      <td>284</td>\n",
       "      <td>580</td>\n",
       "      <td>9617</td>\n",
       "      <td>8456</td>\n",
       "      <td>6791</td>\n",
       "      <td>6327</td>\n",
       "      <td>...</td>\n",
       "      <td>42037</td>\n",
       "      <td>7524</td>\n",
       "      <td>12550</td>\n",
       "      <td>5624</td>\n",
       "      <td>condition</td>\n",
       "      <td>52132</td>\n",
       "      <td>10366.101190</td>\n",
       "      <td>7510.0</td>\n",
       "      <td>11069.781250</td>\n",
       "      <td>1.225401e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>163</td>\n",
       "      <td>535</td>\n",
       "      <td>340</td>\n",
       "      <td>518</td>\n",
       "      <td>260</td>\n",
       "      <td>2345</td>\n",
       "      <td>6019</td>\n",
       "      <td>...</td>\n",
       "      <td>1581</td>\n",
       "      <td>11264</td>\n",
       "      <td>5600</td>\n",
       "      <td>1088</td>\n",
       "      <td>condition</td>\n",
       "      <td>25923</td>\n",
       "      <td>4106.279762</td>\n",
       "      <td>2605.0</td>\n",
       "      <td>4563.488254</td>\n",
       "      <td>2.082543e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>155</td>\n",
       "      <td>145</td>\n",
       "      <td>354</td>\n",
       "      <td>126</td>\n",
       "      <td>124</td>\n",
       "      <td>120</td>\n",
       "      <td>624</td>\n",
       "      <td>241</td>\n",
       "      <td>804</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>8042</td>\n",
       "      <td>6048</td>\n",
       "      <td>4028</td>\n",
       "      <td>8</td>\n",
       "      <td>condition</td>\n",
       "      <td>37775</td>\n",
       "      <td>4572.690476</td>\n",
       "      <td>1016.0</td>\n",
       "      <td>6392.889170</td>\n",
       "      <td>4.086903e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>804</td>\n",
       "      <td>1335</td>\n",
       "      <td>126</td>\n",
       "      <td>4253</td>\n",
       "      <td>1318</td>\n",
       "      <td>926</td>\n",
       "      <td>1901</td>\n",
       "      <td>4419</td>\n",
       "      <td>654</td>\n",
       "      <td>210</td>\n",
       "      <td>...</td>\n",
       "      <td>16382</td>\n",
       "      <td>6956</td>\n",
       "      <td>5749</td>\n",
       "      <td>389</td>\n",
       "      <td>condition</td>\n",
       "      <td>31467</td>\n",
       "      <td>8730.446429</td>\n",
       "      <td>6480.5</td>\n",
       "      <td>8018.226176</td>\n",
       "      <td>6.429195e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>511</td>\n",
       "      <td>2325</td>\n",
       "      <td>580</td>\n",
       "      <td>2808</td>\n",
       "      <td>0</td>\n",
       "      <td>1677</td>\n",
       "      <td>307</td>\n",
       "      <td>3043</td>\n",
       "      <td>1769</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>32513</td>\n",
       "      <td>20643</td>\n",
       "      <td>16746</td>\n",
       "      <td>30018</td>\n",
       "      <td>condition</td>\n",
       "      <td>48617</td>\n",
       "      <td>12539.821429</td>\n",
       "      <td>8618.5</td>\n",
       "      <td>12771.059454</td>\n",
       "      <td>1.631000e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 174 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0:00  1:00   2:00   3:00  4:00   5:00   6:00   7:00   8:00   9:00  ...  \\\n",
       "0     480   245    424    242   733     58    600    822   8804   6687  ...   \n",
       "1    1532  1535    546    270  5704   9447  28610  19627  24468  30029  ...   \n",
       "2    4408  2075    480    480   480    480    480    480    485  19090  ...   \n",
       "3    2220   423    203     28   569    388  11980  17591  16399  22316  ...   \n",
       "4    4835  3959   6457    807  1710    360    532    544    949   9951  ...   \n",
       "5    4594   175    612    192   705    950    307  17239  14846   6839  ...   \n",
       "6    1068   917    606    676   596  34090  17938  14812  28039  33920  ...   \n",
       "7    1386   818   2135    974   241   1026   1812    688   1343   3193  ...   \n",
       "8    2882   871    411   2840  1243    506   1093  11200  21471  25424  ...   \n",
       "9     959   328   1629    641   440    548    346  12782  31878  24143  ...   \n",
       "10   4126   135    258    816   602    465   6962    251    299   2538  ...   \n",
       "11    706  2978    662     47   383    643   4018   5668   4839   3091  ...   \n",
       "12    304   606    316   2275  4103  16187  14692   8681   1295   1176  ...   \n",
       "13    112   340  10844  14721  8324   6310  26737  16852   5452    589  ...   \n",
       "14   1078   224   1091    209   810    676   1440  43040  26806  12270  ...   \n",
       "15    185    65    233    435    34    110     97    516  17279   6196  ...   \n",
       "16  10407   813    383    897   581    314    604    383     30   1682  ...   \n",
       "17   2732  5053   4862   4617  1969    633   2151   1670   2427   2457  ...   \n",
       "18    122   280    399    607   284    580   9617   8456   6791   6327  ...   \n",
       "19      0     0     69    163   535    340    518    260   2345   6019  ...   \n",
       "20    155   145    354    126   124    120    624    241    804     13  ...   \n",
       "21    804  1335    126   4253  1318    926   1901   4419    654    210  ...   \n",
       "22    511  2325    580   2808     0   1677    307   3043   1769   2015  ...   \n",
       "\n",
       "    20:00.6  21:00.6  22:00.6  23:00.6         Id     Max          mean  \\\n",
       "0      5493    12413    11248     4485  condition   68238   9392.732143   \n",
       "1       356     5879     2537     1537  condition   64882  12579.583333   \n",
       "2     20286    11681     2561    19681  condition   68830  15732.833333   \n",
       "3     30383    26798     4657     8929  condition   64887  12277.755952   \n",
       "4      9488     5794     3055    11040  condition   62282   9496.154762   \n",
       "5      7542    23354    28496    11572  condition   56630  11060.553571   \n",
       "6     21216    33127    14813    14132  condition   75525  17277.238095   \n",
       "7     10080    10080     7826     2130  condition  130377  13690.857143   \n",
       "8      5530    24348     9677     6113  condition   47419  10508.839286   \n",
       "9     27730    45805    18419      750  condition   67513  20614.577381   \n",
       "10    26392    14783     2233     9466  condition   42125   7661.291667   \n",
       "11    17444    17556    15250    12628  condition   63559  11032.392857   \n",
       "12    24882    31715    18786    14797  condition   54389  15232.261905   \n",
       "13      178      148     2840        0  condition   44674   4643.047619   \n",
       "14     2154     8280     8312     5281  condition   65955   6912.255952   \n",
       "15     4359     5973     5071    23938  condition   90108  16461.041667   \n",
       "16     8566     2726     4785     4848  condition   16283   4815.428571   \n",
       "17     5129     5050      414       82  condition   16569   4232.446429   \n",
       "18    42037     7524    12550     5624  condition   52132  10366.101190   \n",
       "19     1581    11264     5600     1088  condition   25923   4106.279762   \n",
       "20     8042     6048     4028        8  condition   37775   4572.690476   \n",
       "21    16382     6956     5749      389  condition   31467   8730.446429   \n",
       "22    32513    20643    16746    30018  condition   48617  12539.821429   \n",
       "\n",
       "     median            SD           Var  \n",
       "0    6033.0  11629.952868  1.352558e+08  \n",
       "1    7622.5  13651.806945  1.863718e+08  \n",
       "2   14450.5  14848.824389  2.204876e+08  \n",
       "3   10132.0  11670.505975  1.362007e+08  \n",
       "4    7076.0   9659.991062  9.331543e+07  \n",
       "5    8384.5  11243.680391  1.264203e+08  \n",
       "6   10000.0  20781.392660  4.318663e+08  \n",
       "7    6695.0  17782.014525  3.162000e+08  \n",
       "8    9114.5   9566.698553  9.152172e+07  \n",
       "9   19825.0  17386.567358  3.022927e+08  \n",
       "10   3622.5   9019.642224  8.135395e+07  \n",
       "11   8327.5  10556.284190  1.114351e+08  \n",
       "12  14204.0  12482.881080  1.558223e+08  \n",
       "13   2959.0   5865.685480  3.440627e+07  \n",
       "14   4030.5   9108.537166  8.296545e+07  \n",
       "15  12019.0  17145.700575  2.939750e+08  \n",
       "16   4088.0   4010.180922  1.608155e+07  \n",
       "17   4167.5   3055.384235  9.335373e+06  \n",
       "18   7510.0  11069.781250  1.225401e+08  \n",
       "19   2605.0   4563.488254  2.082543e+07  \n",
       "20   1016.0   6392.889170  4.086903e+07  \n",
       "21   6480.5   8018.226176  6.429195e+07  \n",
       "22   8618.5  12771.059454  1.631000e+08  \n",
       "\n",
       "[23 rows x 174 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df['Max'] = week_columns.max(axis = 1)\n",
    "my_df['mean'] = week_columns.mean(axis=1)\n",
    "my_df['median'] = week_columns.median(axis = 1)\n",
    "my_df['SD'] = week_columns.std(axis =1)\n",
    "my_df['Var'] = week_columns.var(axis =1)\n",
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Max</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>SD</th>\n",
       "      <th>Var</th>\n",
       "      <th>Id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>68238</td>\n",
       "      <td>9392.732143</td>\n",
       "      <td>6033.0</td>\n",
       "      <td>11629.952868</td>\n",
       "      <td>1.352558e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>64882</td>\n",
       "      <td>12579.583333</td>\n",
       "      <td>7622.5</td>\n",
       "      <td>13651.806945</td>\n",
       "      <td>1.863718e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>68830</td>\n",
       "      <td>15732.833333</td>\n",
       "      <td>14450.5</td>\n",
       "      <td>14848.824389</td>\n",
       "      <td>2.204876e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>64887</td>\n",
       "      <td>12277.755952</td>\n",
       "      <td>10132.0</td>\n",
       "      <td>11670.505975</td>\n",
       "      <td>1.362007e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>62282</td>\n",
       "      <td>9496.154762</td>\n",
       "      <td>7076.0</td>\n",
       "      <td>9659.991062</td>\n",
       "      <td>9.331543e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>56630</td>\n",
       "      <td>11060.553571</td>\n",
       "      <td>8384.5</td>\n",
       "      <td>11243.680391</td>\n",
       "      <td>1.264203e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>75525</td>\n",
       "      <td>17277.238095</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>20781.392660</td>\n",
       "      <td>4.318663e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>130377</td>\n",
       "      <td>13690.857143</td>\n",
       "      <td>6695.0</td>\n",
       "      <td>17782.014525</td>\n",
       "      <td>3.162000e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>47419</td>\n",
       "      <td>10508.839286</td>\n",
       "      <td>9114.5</td>\n",
       "      <td>9566.698553</td>\n",
       "      <td>9.152172e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>67513</td>\n",
       "      <td>20614.577381</td>\n",
       "      <td>19825.0</td>\n",
       "      <td>17386.567358</td>\n",
       "      <td>3.022927e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>42125</td>\n",
       "      <td>7661.291667</td>\n",
       "      <td>3622.5</td>\n",
       "      <td>9019.642224</td>\n",
       "      <td>8.135395e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>63559</td>\n",
       "      <td>11032.392857</td>\n",
       "      <td>8327.5</td>\n",
       "      <td>10556.284190</td>\n",
       "      <td>1.114351e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>54389</td>\n",
       "      <td>15232.261905</td>\n",
       "      <td>14204.0</td>\n",
       "      <td>12482.881080</td>\n",
       "      <td>1.558223e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>44674</td>\n",
       "      <td>4643.047619</td>\n",
       "      <td>2959.0</td>\n",
       "      <td>5865.685480</td>\n",
       "      <td>3.440627e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>65955</td>\n",
       "      <td>6912.255952</td>\n",
       "      <td>4030.5</td>\n",
       "      <td>9108.537166</td>\n",
       "      <td>8.296545e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>90108</td>\n",
       "      <td>16461.041667</td>\n",
       "      <td>12019.0</td>\n",
       "      <td>17145.700575</td>\n",
       "      <td>2.939750e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16283</td>\n",
       "      <td>4815.428571</td>\n",
       "      <td>4088.0</td>\n",
       "      <td>4010.180922</td>\n",
       "      <td>1.608155e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>16569</td>\n",
       "      <td>4232.446429</td>\n",
       "      <td>4167.5</td>\n",
       "      <td>3055.384235</td>\n",
       "      <td>9.335373e+06</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>52132</td>\n",
       "      <td>10366.101190</td>\n",
       "      <td>7510.0</td>\n",
       "      <td>11069.781250</td>\n",
       "      <td>1.225401e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>25923</td>\n",
       "      <td>4106.279762</td>\n",
       "      <td>2605.0</td>\n",
       "      <td>4563.488254</td>\n",
       "      <td>2.082543e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>37775</td>\n",
       "      <td>4572.690476</td>\n",
       "      <td>1016.0</td>\n",
       "      <td>6392.889170</td>\n",
       "      <td>4.086903e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>31467</td>\n",
       "      <td>8730.446429</td>\n",
       "      <td>6480.5</td>\n",
       "      <td>8018.226176</td>\n",
       "      <td>6.429195e+07</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>48617</td>\n",
       "      <td>12539.821429</td>\n",
       "      <td>8618.5</td>\n",
       "      <td>12771.059454</td>\n",
       "      <td>1.631000e+08</td>\n",
       "      <td>condition</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Max          mean   median            SD           Var         Id\n",
       "0    68238   9392.732143   6033.0  11629.952868  1.352558e+08  condition\n",
       "1    64882  12579.583333   7622.5  13651.806945  1.863718e+08  condition\n",
       "2    68830  15732.833333  14450.5  14848.824389  2.204876e+08  condition\n",
       "3    64887  12277.755952  10132.0  11670.505975  1.362007e+08  condition\n",
       "4    62282   9496.154762   7076.0   9659.991062  9.331543e+07  condition\n",
       "5    56630  11060.553571   8384.5  11243.680391  1.264203e+08  condition\n",
       "6    75525  17277.238095  10000.0  20781.392660  4.318663e+08  condition\n",
       "7   130377  13690.857143   6695.0  17782.014525  3.162000e+08  condition\n",
       "8    47419  10508.839286   9114.5   9566.698553  9.152172e+07  condition\n",
       "9    67513  20614.577381  19825.0  17386.567358  3.022927e+08  condition\n",
       "10   42125   7661.291667   3622.5   9019.642224  8.135395e+07  condition\n",
       "11   63559  11032.392857   8327.5  10556.284190  1.114351e+08  condition\n",
       "12   54389  15232.261905  14204.0  12482.881080  1.558223e+08  condition\n",
       "13   44674   4643.047619   2959.0   5865.685480  3.440627e+07  condition\n",
       "14   65955   6912.255952   4030.5   9108.537166  8.296545e+07  condition\n",
       "15   90108  16461.041667  12019.0  17145.700575  2.939750e+08  condition\n",
       "16   16283   4815.428571   4088.0   4010.180922  1.608155e+07  condition\n",
       "17   16569   4232.446429   4167.5   3055.384235  9.335373e+06  condition\n",
       "18   52132  10366.101190   7510.0  11069.781250  1.225401e+08  condition\n",
       "19   25923   4106.279762   2605.0   4563.488254  2.082543e+07  condition\n",
       "20   37775   4572.690476   1016.0   6392.889170  4.086903e+07  condition\n",
       "21   31467   8730.446429   6480.5   8018.226176  6.429195e+07  condition\n",
       "22   48617  12539.821429   8618.5  12771.059454  1.631000e+08  condition"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_df = my_df[['Max','mean', 'median','SD', 'Var', 'Id']]\n",
    "feature_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feature_df.to_csv('one_week_condition_features.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#my_df.to_csv('condition_one_week_dataframe.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_df = my_df.drop(my_df.iloc[:, 24:168], axis =1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0:00</th>\n",
       "      <th>1:00</th>\n",
       "      <th>2:00</th>\n",
       "      <th>3:00</th>\n",
       "      <th>4:00</th>\n",
       "      <th>5:00</th>\n",
       "      <th>6:00</th>\n",
       "      <th>7:00</th>\n",
       "      <th>8:00</th>\n",
       "      <th>9:00</th>\n",
       "      <th>...</th>\n",
       "      <th>20:00</th>\n",
       "      <th>21:00</th>\n",
       "      <th>22:00</th>\n",
       "      <th>23:00</th>\n",
       "      <th>Id</th>\n",
       "      <th>Max</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>SD</th>\n",
       "      <th>Var</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>480</td>\n",
       "      <td>245</td>\n",
       "      <td>424</td>\n",
       "      <td>242</td>\n",
       "      <td>733</td>\n",
       "      <td>58</td>\n",
       "      <td>600</td>\n",
       "      <td>822</td>\n",
       "      <td>8804</td>\n",
       "      <td>6687</td>\n",
       "      <td>...</td>\n",
       "      <td>9859</td>\n",
       "      <td>7203</td>\n",
       "      <td>2791</td>\n",
       "      <td>4072</td>\n",
       "      <td>condition</td>\n",
       "      <td>68238</td>\n",
       "      <td>9392.732143</td>\n",
       "      <td>6033.0</td>\n",
       "      <td>11629.952868</td>\n",
       "      <td>1.352558e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1532</td>\n",
       "      <td>1535</td>\n",
       "      <td>546</td>\n",
       "      <td>270</td>\n",
       "      <td>5704</td>\n",
       "      <td>9447</td>\n",
       "      <td>28610</td>\n",
       "      <td>19627</td>\n",
       "      <td>24468</td>\n",
       "      <td>30029</td>\n",
       "      <td>...</td>\n",
       "      <td>2279</td>\n",
       "      <td>24152</td>\n",
       "      <td>1160</td>\n",
       "      <td>283</td>\n",
       "      <td>condition</td>\n",
       "      <td>64882</td>\n",
       "      <td>12579.583333</td>\n",
       "      <td>7622.5</td>\n",
       "      <td>13651.806945</td>\n",
       "      <td>1.863718e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4408</td>\n",
       "      <td>2075</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>485</td>\n",
       "      <td>19090</td>\n",
       "      <td>...</td>\n",
       "      <td>19797</td>\n",
       "      <td>33566</td>\n",
       "      <td>14499</td>\n",
       "      <td>16344</td>\n",
       "      <td>condition</td>\n",
       "      <td>68830</td>\n",
       "      <td>15732.833333</td>\n",
       "      <td>14450.5</td>\n",
       "      <td>14848.824389</td>\n",
       "      <td>2.204876e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2220</td>\n",
       "      <td>423</td>\n",
       "      <td>203</td>\n",
       "      <td>28</td>\n",
       "      <td>569</td>\n",
       "      <td>388</td>\n",
       "      <td>11980</td>\n",
       "      <td>17591</td>\n",
       "      <td>16399</td>\n",
       "      <td>22316</td>\n",
       "      <td>...</td>\n",
       "      <td>25630</td>\n",
       "      <td>46288</td>\n",
       "      <td>39667</td>\n",
       "      <td>28332</td>\n",
       "      <td>condition</td>\n",
       "      <td>64887</td>\n",
       "      <td>12277.755952</td>\n",
       "      <td>10132.0</td>\n",
       "      <td>11670.505975</td>\n",
       "      <td>1.362007e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4835</td>\n",
       "      <td>3959</td>\n",
       "      <td>6457</td>\n",
       "      <td>807</td>\n",
       "      <td>1710</td>\n",
       "      <td>360</td>\n",
       "      <td>532</td>\n",
       "      <td>544</td>\n",
       "      <td>949</td>\n",
       "      <td>9951</td>\n",
       "      <td>...</td>\n",
       "      <td>8858</td>\n",
       "      <td>6839</td>\n",
       "      <td>16246</td>\n",
       "      <td>14172</td>\n",
       "      <td>condition</td>\n",
       "      <td>62282</td>\n",
       "      <td>9496.154762</td>\n",
       "      <td>7076.0</td>\n",
       "      <td>9659.991062</td>\n",
       "      <td>9.331543e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4594</td>\n",
       "      <td>175</td>\n",
       "      <td>612</td>\n",
       "      <td>192</td>\n",
       "      <td>705</td>\n",
       "      <td>950</td>\n",
       "      <td>307</td>\n",
       "      <td>17239</td>\n",
       "      <td>14846</td>\n",
       "      <td>6839</td>\n",
       "      <td>...</td>\n",
       "      <td>6484</td>\n",
       "      <td>4104</td>\n",
       "      <td>6206</td>\n",
       "      <td>10447</td>\n",
       "      <td>condition</td>\n",
       "      <td>56630</td>\n",
       "      <td>11060.553571</td>\n",
       "      <td>8384.5</td>\n",
       "      <td>11243.680391</td>\n",
       "      <td>1.264203e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1068</td>\n",
       "      <td>917</td>\n",
       "      <td>606</td>\n",
       "      <td>676</td>\n",
       "      <td>596</td>\n",
       "      <td>34090</td>\n",
       "      <td>17938</td>\n",
       "      <td>14812</td>\n",
       "      <td>28039</td>\n",
       "      <td>33920</td>\n",
       "      <td>...</td>\n",
       "      <td>10405</td>\n",
       "      <td>17734</td>\n",
       "      <td>11928</td>\n",
       "      <td>15147</td>\n",
       "      <td>condition</td>\n",
       "      <td>75525</td>\n",
       "      <td>17277.238095</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>20781.392660</td>\n",
       "      <td>4.318663e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1386</td>\n",
       "      <td>818</td>\n",
       "      <td>2135</td>\n",
       "      <td>974</td>\n",
       "      <td>241</td>\n",
       "      <td>1026</td>\n",
       "      <td>1812</td>\n",
       "      <td>688</td>\n",
       "      <td>1343</td>\n",
       "      <td>3193</td>\n",
       "      <td>...</td>\n",
       "      <td>19397</td>\n",
       "      <td>13320</td>\n",
       "      <td>28790</td>\n",
       "      <td>3784</td>\n",
       "      <td>condition</td>\n",
       "      <td>130377</td>\n",
       "      <td>13690.857143</td>\n",
       "      <td>6695.0</td>\n",
       "      <td>17782.014525</td>\n",
       "      <td>3.162000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2882</td>\n",
       "      <td>871</td>\n",
       "      <td>411</td>\n",
       "      <td>2840</td>\n",
       "      <td>1243</td>\n",
       "      <td>506</td>\n",
       "      <td>1093</td>\n",
       "      <td>11200</td>\n",
       "      <td>21471</td>\n",
       "      <td>25424</td>\n",
       "      <td>...</td>\n",
       "      <td>10545</td>\n",
       "      <td>19962</td>\n",
       "      <td>8731</td>\n",
       "      <td>14398</td>\n",
       "      <td>condition</td>\n",
       "      <td>47419</td>\n",
       "      <td>10508.839286</td>\n",
       "      <td>9114.5</td>\n",
       "      <td>9566.698553</td>\n",
       "      <td>9.152172e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>959</td>\n",
       "      <td>328</td>\n",
       "      <td>1629</td>\n",
       "      <td>641</td>\n",
       "      <td>440</td>\n",
       "      <td>548</td>\n",
       "      <td>346</td>\n",
       "      <td>12782</td>\n",
       "      <td>31878</td>\n",
       "      <td>24143</td>\n",
       "      <td>...</td>\n",
       "      <td>31324</td>\n",
       "      <td>26594</td>\n",
       "      <td>36162</td>\n",
       "      <td>4696</td>\n",
       "      <td>condition</td>\n",
       "      <td>67513</td>\n",
       "      <td>20614.577381</td>\n",
       "      <td>19825.0</td>\n",
       "      <td>17386.567358</td>\n",
       "      <td>3.022927e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4126</td>\n",
       "      <td>135</td>\n",
       "      <td>258</td>\n",
       "      <td>816</td>\n",
       "      <td>602</td>\n",
       "      <td>465</td>\n",
       "      <td>6962</td>\n",
       "      <td>251</td>\n",
       "      <td>299</td>\n",
       "      <td>2538</td>\n",
       "      <td>...</td>\n",
       "      <td>25566</td>\n",
       "      <td>5649</td>\n",
       "      <td>1337</td>\n",
       "      <td>12736</td>\n",
       "      <td>condition</td>\n",
       "      <td>42125</td>\n",
       "      <td>7661.291667</td>\n",
       "      <td>3622.5</td>\n",
       "      <td>9019.642224</td>\n",
       "      <td>8.135395e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>706</td>\n",
       "      <td>2978</td>\n",
       "      <td>662</td>\n",
       "      <td>47</td>\n",
       "      <td>383</td>\n",
       "      <td>643</td>\n",
       "      <td>4018</td>\n",
       "      <td>5668</td>\n",
       "      <td>4839</td>\n",
       "      <td>3091</td>\n",
       "      <td>...</td>\n",
       "      <td>7570</td>\n",
       "      <td>17972</td>\n",
       "      <td>10805</td>\n",
       "      <td>2961</td>\n",
       "      <td>condition</td>\n",
       "      <td>63559</td>\n",
       "      <td>11032.392857</td>\n",
       "      <td>8327.5</td>\n",
       "      <td>10556.284190</td>\n",
       "      <td>1.114351e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>304</td>\n",
       "      <td>606</td>\n",
       "      <td>316</td>\n",
       "      <td>2275</td>\n",
       "      <td>4103</td>\n",
       "      <td>16187</td>\n",
       "      <td>14692</td>\n",
       "      <td>8681</td>\n",
       "      <td>1295</td>\n",
       "      <td>1176</td>\n",
       "      <td>...</td>\n",
       "      <td>25728</td>\n",
       "      <td>15069</td>\n",
       "      <td>22032</td>\n",
       "      <td>23155</td>\n",
       "      <td>condition</td>\n",
       "      <td>54389</td>\n",
       "      <td>15232.261905</td>\n",
       "      <td>14204.0</td>\n",
       "      <td>12482.881080</td>\n",
       "      <td>1.558223e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>112</td>\n",
       "      <td>340</td>\n",
       "      <td>10844</td>\n",
       "      <td>14721</td>\n",
       "      <td>8324</td>\n",
       "      <td>6310</td>\n",
       "      <td>26737</td>\n",
       "      <td>16852</td>\n",
       "      <td>5452</td>\n",
       "      <td>589</td>\n",
       "      <td>...</td>\n",
       "      <td>3079</td>\n",
       "      <td>414</td>\n",
       "      <td>1256</td>\n",
       "      <td>71</td>\n",
       "      <td>condition</td>\n",
       "      <td>44674</td>\n",
       "      <td>4643.047619</td>\n",
       "      <td>2959.0</td>\n",
       "      <td>5865.685480</td>\n",
       "      <td>3.440627e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1078</td>\n",
       "      <td>224</td>\n",
       "      <td>1091</td>\n",
       "      <td>209</td>\n",
       "      <td>810</td>\n",
       "      <td>676</td>\n",
       "      <td>1440</td>\n",
       "      <td>43040</td>\n",
       "      <td>26806</td>\n",
       "      <td>12270</td>\n",
       "      <td>...</td>\n",
       "      <td>10560</td>\n",
       "      <td>14107</td>\n",
       "      <td>4088</td>\n",
       "      <td>8780</td>\n",
       "      <td>condition</td>\n",
       "      <td>65955</td>\n",
       "      <td>6912.255952</td>\n",
       "      <td>4030.5</td>\n",
       "      <td>9108.537166</td>\n",
       "      <td>8.296545e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>185</td>\n",
       "      <td>65</td>\n",
       "      <td>233</td>\n",
       "      <td>435</td>\n",
       "      <td>34</td>\n",
       "      <td>110</td>\n",
       "      <td>97</td>\n",
       "      <td>516</td>\n",
       "      <td>17279</td>\n",
       "      <td>6196</td>\n",
       "      <td>...</td>\n",
       "      <td>23026</td>\n",
       "      <td>6671</td>\n",
       "      <td>3486</td>\n",
       "      <td>15264</td>\n",
       "      <td>condition</td>\n",
       "      <td>90108</td>\n",
       "      <td>16461.041667</td>\n",
       "      <td>12019.0</td>\n",
       "      <td>17145.700575</td>\n",
       "      <td>2.939750e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10407</td>\n",
       "      <td>813</td>\n",
       "      <td>383</td>\n",
       "      <td>897</td>\n",
       "      <td>581</td>\n",
       "      <td>314</td>\n",
       "      <td>604</td>\n",
       "      <td>383</td>\n",
       "      <td>30</td>\n",
       "      <td>1682</td>\n",
       "      <td>...</td>\n",
       "      <td>1875</td>\n",
       "      <td>4451</td>\n",
       "      <td>2211</td>\n",
       "      <td>3803</td>\n",
       "      <td>condition</td>\n",
       "      <td>16283</td>\n",
       "      <td>4815.428571</td>\n",
       "      <td>4088.0</td>\n",
       "      <td>4010.180922</td>\n",
       "      <td>1.608155e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2732</td>\n",
       "      <td>5053</td>\n",
       "      <td>4862</td>\n",
       "      <td>4617</td>\n",
       "      <td>1969</td>\n",
       "      <td>633</td>\n",
       "      <td>2151</td>\n",
       "      <td>1670</td>\n",
       "      <td>2427</td>\n",
       "      <td>2457</td>\n",
       "      <td>...</td>\n",
       "      <td>4959</td>\n",
       "      <td>2672</td>\n",
       "      <td>95</td>\n",
       "      <td>4683</td>\n",
       "      <td>condition</td>\n",
       "      <td>16569</td>\n",
       "      <td>4232.446429</td>\n",
       "      <td>4167.5</td>\n",
       "      <td>3055.384235</td>\n",
       "      <td>9.335373e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>122</td>\n",
       "      <td>280</td>\n",
       "      <td>399</td>\n",
       "      <td>607</td>\n",
       "      <td>284</td>\n",
       "      <td>580</td>\n",
       "      <td>9617</td>\n",
       "      <td>8456</td>\n",
       "      <td>6791</td>\n",
       "      <td>6327</td>\n",
       "      <td>...</td>\n",
       "      <td>7009</td>\n",
       "      <td>7239</td>\n",
       "      <td>2955</td>\n",
       "      <td>5045</td>\n",
       "      <td>condition</td>\n",
       "      <td>52132</td>\n",
       "      <td>10366.101190</td>\n",
       "      <td>7510.0</td>\n",
       "      <td>11069.781250</td>\n",
       "      <td>1.225401e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>163</td>\n",
       "      <td>535</td>\n",
       "      <td>340</td>\n",
       "      <td>518</td>\n",
       "      <td>260</td>\n",
       "      <td>2345</td>\n",
       "      <td>6019</td>\n",
       "      <td>...</td>\n",
       "      <td>1076</td>\n",
       "      <td>7168</td>\n",
       "      <td>793</td>\n",
       "      <td>31</td>\n",
       "      <td>condition</td>\n",
       "      <td>25923</td>\n",
       "      <td>4106.279762</td>\n",
       "      <td>2605.0</td>\n",
       "      <td>4563.488254</td>\n",
       "      <td>2.082543e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>155</td>\n",
       "      <td>145</td>\n",
       "      <td>354</td>\n",
       "      <td>126</td>\n",
       "      <td>124</td>\n",
       "      <td>120</td>\n",
       "      <td>624</td>\n",
       "      <td>241</td>\n",
       "      <td>804</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>390</td>\n",
       "      <td>1838</td>\n",
       "      <td>3121</td>\n",
       "      <td>3720</td>\n",
       "      <td>condition</td>\n",
       "      <td>37775</td>\n",
       "      <td>4572.690476</td>\n",
       "      <td>1016.0</td>\n",
       "      <td>6392.889170</td>\n",
       "      <td>4.086903e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>804</td>\n",
       "      <td>1335</td>\n",
       "      <td>126</td>\n",
       "      <td>4253</td>\n",
       "      <td>1318</td>\n",
       "      <td>926</td>\n",
       "      <td>1901</td>\n",
       "      <td>4419</td>\n",
       "      <td>654</td>\n",
       "      <td>210</td>\n",
       "      <td>...</td>\n",
       "      <td>15582</td>\n",
       "      <td>16356</td>\n",
       "      <td>9316</td>\n",
       "      <td>382</td>\n",
       "      <td>condition</td>\n",
       "      <td>31467</td>\n",
       "      <td>8730.446429</td>\n",
       "      <td>6480.5</td>\n",
       "      <td>8018.226176</td>\n",
       "      <td>6.429195e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>511</td>\n",
       "      <td>2325</td>\n",
       "      <td>580</td>\n",
       "      <td>2808</td>\n",
       "      <td>0</td>\n",
       "      <td>1677</td>\n",
       "      <td>307</td>\n",
       "      <td>3043</td>\n",
       "      <td>1769</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>12866</td>\n",
       "      <td>12158</td>\n",
       "      <td>7207</td>\n",
       "      <td>11124</td>\n",
       "      <td>condition</td>\n",
       "      <td>48617</td>\n",
       "      <td>12539.821429</td>\n",
       "      <td>8618.5</td>\n",
       "      <td>12771.059454</td>\n",
       "      <td>1.631000e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0:00  1:00   2:00   3:00  4:00   5:00   6:00   7:00   8:00   9:00  ...  \\\n",
       "0     480   245    424    242   733     58    600    822   8804   6687  ...   \n",
       "1    1532  1535    546    270  5704   9447  28610  19627  24468  30029  ...   \n",
       "2    4408  2075    480    480   480    480    480    480    485  19090  ...   \n",
       "3    2220   423    203     28   569    388  11980  17591  16399  22316  ...   \n",
       "4    4835  3959   6457    807  1710    360    532    544    949   9951  ...   \n",
       "5    4594   175    612    192   705    950    307  17239  14846   6839  ...   \n",
       "6    1068   917    606    676   596  34090  17938  14812  28039  33920  ...   \n",
       "7    1386   818   2135    974   241   1026   1812    688   1343   3193  ...   \n",
       "8    2882   871    411   2840  1243    506   1093  11200  21471  25424  ...   \n",
       "9     959   328   1629    641   440    548    346  12782  31878  24143  ...   \n",
       "10   4126   135    258    816   602    465   6962    251    299   2538  ...   \n",
       "11    706  2978    662     47   383    643   4018   5668   4839   3091  ...   \n",
       "12    304   606    316   2275  4103  16187  14692   8681   1295   1176  ...   \n",
       "13    112   340  10844  14721  8324   6310  26737  16852   5452    589  ...   \n",
       "14   1078   224   1091    209   810    676   1440  43040  26806  12270  ...   \n",
       "15    185    65    233    435    34    110     97    516  17279   6196  ...   \n",
       "16  10407   813    383    897   581    314    604    383     30   1682  ...   \n",
       "17   2732  5053   4862   4617  1969    633   2151   1670   2427   2457  ...   \n",
       "18    122   280    399    607   284    580   9617   8456   6791   6327  ...   \n",
       "19      0     0     69    163   535    340    518    260   2345   6019  ...   \n",
       "20    155   145    354    126   124    120    624    241    804     13  ...   \n",
       "21    804  1335    126   4253  1318    926   1901   4419    654    210  ...   \n",
       "22    511  2325    580   2808     0   1677    307   3043   1769   2015  ...   \n",
       "\n",
       "    20:00  21:00  22:00  23:00         Id     Max          mean   median  \\\n",
       "0    9859   7203   2791   4072  condition   68238   9392.732143   6033.0   \n",
       "1    2279  24152   1160    283  condition   64882  12579.583333   7622.5   \n",
       "2   19797  33566  14499  16344  condition   68830  15732.833333  14450.5   \n",
       "3   25630  46288  39667  28332  condition   64887  12277.755952  10132.0   \n",
       "4    8858   6839  16246  14172  condition   62282   9496.154762   7076.0   \n",
       "5    6484   4104   6206  10447  condition   56630  11060.553571   8384.5   \n",
       "6   10405  17734  11928  15147  condition   75525  17277.238095  10000.0   \n",
       "7   19397  13320  28790   3784  condition  130377  13690.857143   6695.0   \n",
       "8   10545  19962   8731  14398  condition   47419  10508.839286   9114.5   \n",
       "9   31324  26594  36162   4696  condition   67513  20614.577381  19825.0   \n",
       "10  25566   5649   1337  12736  condition   42125   7661.291667   3622.5   \n",
       "11   7570  17972  10805   2961  condition   63559  11032.392857   8327.5   \n",
       "12  25728  15069  22032  23155  condition   54389  15232.261905  14204.0   \n",
       "13   3079    414   1256     71  condition   44674   4643.047619   2959.0   \n",
       "14  10560  14107   4088   8780  condition   65955   6912.255952   4030.5   \n",
       "15  23026   6671   3486  15264  condition   90108  16461.041667  12019.0   \n",
       "16   1875   4451   2211   3803  condition   16283   4815.428571   4088.0   \n",
       "17   4959   2672     95   4683  condition   16569   4232.446429   4167.5   \n",
       "18   7009   7239   2955   5045  condition   52132  10366.101190   7510.0   \n",
       "19   1076   7168    793     31  condition   25923   4106.279762   2605.0   \n",
       "20    390   1838   3121   3720  condition   37775   4572.690476   1016.0   \n",
       "21  15582  16356   9316    382  condition   31467   8730.446429   6480.5   \n",
       "22  12866  12158   7207  11124  condition   48617  12539.821429   8618.5   \n",
       "\n",
       "              SD           Var  \n",
       "0   11629.952868  1.352558e+08  \n",
       "1   13651.806945  1.863718e+08  \n",
       "2   14848.824389  2.204876e+08  \n",
       "3   11670.505975  1.362007e+08  \n",
       "4    9659.991062  9.331543e+07  \n",
       "5   11243.680391  1.264203e+08  \n",
       "6   20781.392660  4.318663e+08  \n",
       "7   17782.014525  3.162000e+08  \n",
       "8    9566.698553  9.152172e+07  \n",
       "9   17386.567358  3.022927e+08  \n",
       "10   9019.642224  8.135395e+07  \n",
       "11  10556.284190  1.114351e+08  \n",
       "12  12482.881080  1.558223e+08  \n",
       "13   5865.685480  3.440627e+07  \n",
       "14   9108.537166  8.296545e+07  \n",
       "15  17145.700575  2.939750e+08  \n",
       "16   4010.180922  1.608155e+07  \n",
       "17   3055.384235  9.335373e+06  \n",
       "18  11069.781250  1.225401e+08  \n",
       "19   4563.488254  2.082543e+07  \n",
       "20   6392.889170  4.086903e+07  \n",
       "21   8018.226176  6.429195e+07  \n",
       "22  12771.059454  1.631000e+08  \n",
       "\n",
       "[23 rows x 30 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "#my_df.to_csv(\"first_day_condition.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>date</th>\n",
       "      <th>activity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2003-05-07 12:00:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003-05-07 12:01:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2003-05-07 12:02:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2003-05-07 12:03:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2003-05-07 12:04:00</td>\n",
       "      <td>2003-05-07</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
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       "      <th>23243</th>\n",
       "      <td>2003-05-23 15:23:00</td>\n",
       "      <td>2003-05-23</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>23244 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 timestamp        date  activity\n",
       "0      2003-05-07 12:00:00  2003-05-07         0\n",
       "1      2003-05-07 12:01:00  2003-05-07       143\n",
       "2      2003-05-07 12:02:00  2003-05-07         0\n",
       "3      2003-05-07 12:03:00  2003-05-07        20\n",
       "4      2003-05-07 12:04:00  2003-05-07       166\n",
       "...                    ...         ...       ...\n",
       "23239  2003-05-23 15:19:00  2003-05-23         0\n",
       "23240  2003-05-23 15:20:00  2003-05-23         0\n",
       "23241  2003-05-23 15:21:00  2003-05-23         0\n",
       "23242  2003-05-23 15:22:00  2003-05-23         0\n",
       "23243  2003-05-23 15:23:00  2003-05-23       533\n",
       "\n",
       "[23244 rows x 3 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df= pd.read_csv('condition_1.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "                 timestamp        date  activity           Id\n",
       "30     2003-05-07 12:30:00  2003-05-07       398  condition_1\n",
       "31     2003-05-07 12:31:00  2003-05-07       469  condition_1\n",
       "32     2003-05-07 12:32:00  2003-05-07       190  condition_1\n",
       "33     2003-05-07 12:33:00  2003-05-07       242  condition_1\n",
       "34     2003-05-07 12:34:00  2003-05-07       242  condition_1\n",
       "...                    ...         ...       ...          ...\n",
       "17306  2003-05-19 12:26:00  2003-05-19       862  condition_1\n",
       "17307  2003-05-19 12:27:00  2003-05-19       102  condition_1\n",
       "17308  2003-05-19 12:28:00  2003-05-19        49  condition_1\n",
       "17309  2003-05-19 12:29:00  2003-05-19        61  condition_1\n",
       "17310  2003-05-19 12:30:00  2003-05-19        76  condition_1\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "my_df= df.drop(df.index[0: 30])\n",
    "\n",
    "#starting patient 1 from 12:00am \n",
    "my_df= my_df.drop(df.index[17311:23245])\n",
    "\n",
    "#creating an ID tag for patient 1\n",
    "\n",
    "my_df['Id'] =np.nan\n",
    "my_df['Id'].fillna('condition_1', inplace= True)\n",
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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      ],
      "text/plain": [
       "timestamp  13:00  14:00  15:00  16:00  17:00  18:00 19:00 20:00 21:00 22:00  \\\n",
       "0          10971  17074  16751  13127  14313  12591  7747  3628  5997  2492   \n",
       "\n",
       "timestamp  ... 04:00 05:00 06:00 07:00 08:00  09:00  10:00  11:00  12:00  Id  \n",
       "0          ...   253   415  1053   708  1519  13420  11455  13541  21750 NaN  \n",
       "\n",
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     },
     "execution_count": 49,
     "metadata": {},
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   ],
   "source": [
    "one_df = load_hourly_activity(my_df)\n",
    "one_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "                 timestamp        date  activity           Id\n",
       "1290   2003-05-08 12:30:00  2003-05-08       337  condition_2\n",
       "1291   2003-05-08 12:31:00  2003-05-08       438  condition_2\n",
       "1292   2003-05-08 12:32:00  2003-05-08       372  condition_2\n",
       "1293   2003-05-08 12:33:00  2003-05-08       397  condition_2\n",
       "1294   2003-05-08 12:34:00  2003-05-08       250  condition_2\n",
       "...                    ...         ...       ...          ...\n",
       "18566  2003-05-20 12:26:00  2003-05-20         6  condition_2\n",
       "18567  2003-05-20 12:27:00  2003-05-20        22  condition_2\n",
       "18568  2003-05-20 12:28:00  2003-05-20        62  condition_2\n",
       "18569  2003-05-20 12:29:00  2003-05-20        21  condition_2\n",
       "18570  2003-05-20 12:30:00  2003-05-20         6  condition_2\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "two_df= pd.read_csv('condition_2.csv')\n",
    "two_df= two_df.drop(two_df.index[0: 1290])\n",
    "two_df= two_df.drop(two_df.index[17281: 38974])\n",
    "two_df['Id'] =np.nan\n",
    "two_df['Id'].fillna('condition_2', inplace= True)\n",
    "two_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 289 columns</p>\n",
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      ],
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       "timestamp  13:00  14:00  15:00  16:00  17:00  18:00 19:00 20:00 21:00  22:00  \\\n",
       "0          12092  30845  23816  29557  23204  15980  9892  8865  2279  24152   \n",
       "\n",
       "timestamp  ... 04:00 05:00 06:00  07:00  08:00  09:00  10:00  11:00  12:00  Id  \n",
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       "\n",
       "[1 rows x 289 columns]"
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     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "two_df = load_hourly_activity(two_df)\n",
    "two_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3"
   ]
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  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
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       "             timestamp       date  activity           Id\n",
       "1290   5/20/2003 12:30  5/20/2003         8  condition_3\n",
       "1291   5/20/2003 12:31  5/20/2003        37  condition_3\n",
       "1292   5/20/2003 12:32  5/20/2003        70  condition_3\n",
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       "1294   5/20/2003 12:34  5/20/2003       293  condition_3\n",
       "...                ...        ...       ...          ...\n",
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       "18570   6/1/2003 12:30   6/1/2003       620  condition_3\n",
       "\n",
       "[17281 rows x 4 columns]"
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     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "three_df= pd.read_csv('condition_3.csv')\n",
    "three_df= three_df.drop(three_df.index[0: 1290])\n",
    "three_df= three_df.drop(three_df.index[17281: 65408])\n",
    "three_df['Id'] =np.nan\n",
    "three_df['Id'].fillna('condition_3', inplace= True)\n",
    "three_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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   "source": [
    "three_df = load_hourly_activity(three_df)  \n",
    "three_df"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4"
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   "execution_count": 65,
   "metadata": {},
   "outputs": [
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       "                 timestamp        date  activity           Id\n",
       "31     2003-06-03 12:30:00  2003-06-03        32  condition_4\n",
       "32     2003-06-03 12:31:00  2003-06-03        47  condition_4\n",
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       "...                    ...         ...       ...          ...\n",
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       "17311  2003-06-15 12:30:00  2003-06-15       243  condition_4\n",
       "\n",
       "[17281 rows x 4 columns]"
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     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "four_df= pd.read_csv('condition_4.csv')\n",
    "four_df= four_df.drop(four_df.index[0: 31])\n",
    "four_df= four_df.drop(four_df.index[17281: 38927])\n",
    "four_df['Id'] =np.nan\n",
    "four_df['Id'].fillna('condition_4', inplace= True)\n",
    "four_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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       "timestamp 13:00  14:00  15:00  16:00  17:00 18:00 19:00  20:00  21:00  22:00  \\\n",
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     "execution_count": 66,
     "metadata": {},
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   "source": [
    "four_df = load_hourly_activity(four_df)  \n",
    "four_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
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       "      <td>2003-06-12</td>\n",
       "      <td>0</td>\n",
       "      <td>condition_5</td>\n",
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       "      <th>124</th>\n",
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       "      <th>17396</th>\n",
       "      <td>2003-06-24 12:26:00</td>\n",
       "      <td>2003-06-24</td>\n",
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       "      <th>17397</th>\n",
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       "      <td>2003-06-24</td>\n",
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      ],
      "text/plain": [
       "                 timestamp        date  activity           Id\n",
       "120    2003-06-12 12:30:00  2003-06-12         0  condition_5\n",
       "121    2003-06-12 12:31:00  2003-06-12         0  condition_5\n",
       "122    2003-06-12 12:32:00  2003-06-12         0  condition_5\n",
       "123    2003-06-12 12:33:00  2003-06-12         0  condition_5\n",
       "124    2003-06-12 12:34:00  2003-06-12       132  condition_5\n",
       "...                    ...         ...       ...          ...\n",
       "17396  2003-06-24 12:26:00  2003-06-24       784  condition_5\n",
       "17397  2003-06-24 12:27:00  2003-06-24       122  condition_5\n",
       "17398  2003-06-24 12:28:00  2003-06-24        28  condition_5\n",
       "17399  2003-06-24 12:29:00  2003-06-24         6  condition_5\n",
       "17400  2003-06-24 12:30:00  2003-06-24        40  condition_5\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "five_df= pd.read_csv('condition_5.csv')\n",
    "five_df= five_df.drop(five_df.index[0: 120])\n",
    "five_df= five_df.drop(five_df.index[17281: 47494])\n",
    "five_df['Id'] =np.nan\n",
    "five_df['Id'].fillna('condition_5', inplace= True)\n",
    "five_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "execution_count": 69,
     "metadata": {},
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   "source": [
    "five_df = load_hourly_activity(five_df)  \n",
    "five_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6"
   ]
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  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
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       "                 timestamp        date  activity           Id\n",
       "30     2003-08-19 12:30:00  2003-08-19         0  condition_6\n",
       "31     2003-08-19 12:31:00  2003-08-19         0  condition_6\n",
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       "...                    ...         ...       ...          ...\n",
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       "17310  2003-08-31 12:30:00  2003-08-31       782  condition_6\n",
       "\n",
       "[17281 rows x 4 columns]"
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     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "six_df= pd.read_csv('condition_6.csv')\n",
    "six_df= six_df.drop(six_df.index[0: 30])\n",
    "six_df= six_df.drop(six_df.index[17281: 51590])\n",
    "six_df['Id'] =np.nan\n",
    "six_df['Id'].fillna('condition_6', inplace = True)\n",
    "six_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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      "text/plain": [
       "timestamp 13:00 14:00  15:00  16:00  17:00  18:00  19:00  20:00  21:00  22:00  \\\n",
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     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "six_df = load_hourly_activity(six_df) \n",
    "six_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
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       "      <th>17429</th>\n",
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       "      <td>2004-05-16</td>\n",
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       "  </tbody>\n",
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       "<p>17281 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 timestamp        date  activity           Id\n",
       "150    2004-05-04 12:30:00  2004-05-04        57  condition_7\n",
       "151    2004-05-04 12:31:00  2004-05-04        53  condition_7\n",
       "152    2004-05-04 12:32:00  2004-05-04       357  condition_7\n",
       "153    2004-05-04 12:33:00  2004-05-04       564  condition_7\n",
       "154    2004-05-04 12:34:00  2004-05-04      1102  condition_7\n",
       "...                    ...         ...       ...          ...\n",
       "17426  2004-05-16 12:26:00  2004-05-16        13  condition_7\n",
       "17427  2004-05-16 12:27:00  2004-05-16        42  condition_7\n",
       "17428  2004-05-16 12:28:00  2004-05-16       146  condition_7\n",
       "17429  2004-05-16 12:29:00  2004-05-16        43  condition_7\n",
       "17430  2004-05-16 12:30:00  2004-05-16        22  condition_7\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seven_df= pd.read_csv('condition_7.csv')\n",
    "seven_df= seven_df.drop(seven_df.index[0: 150])\n",
    "seven_df= seven_df.drop(seven_df.index[17281: 51491])\n",
    "seven_df['Id'] =np.nan\n",
    "seven_df['Id'].fillna('condition_7', inplace = True)\n",
    "seven_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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       "timestamp 13:00  14:00  15:00 16:00 17:00  18:00  19:00  20:00  21:00  22:00  \\\n",
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     "execution_count": 79,
     "metadata": {},
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   "source": [
    "seven_df = load_hourly_activity(seven_df) \n",
    "seven_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 8"
   ]
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  {
   "cell_type": "code",
   "execution_count": 81,
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       "                 timestamp        date  activity           Id\n",
       "150    2004-05-06 12:30:00  2004-05-06         3  condition_8\n",
       "151    2004-05-06 12:31:00  2004-05-06         0  condition_8\n",
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       "...                    ...         ...       ...          ...\n",
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       "17430  2004-05-18 12:30:00  2004-05-18         3  condition_8\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eight_df= pd.read_csv('condition_8.csv')\n",
    "eight_df= eight_df.drop(eight_df.index[0: 150])\n",
    "eight_df= eight_df.drop(eight_df.index[17281: 28919])\n",
    "eight_df['Id'] =np.nan\n",
    "eight_df['Id'].fillna('condition_8', inplace= True)\n",
    "eight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "eight_df = load_hourly_activity(eight_df)\n",
    "eight_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
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       "      <td>23</td>\n",
       "      <td>condition_9</td>\n",
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       "      <th>17279</th>\n",
       "      <td>2004-06-08 12:29:00</td>\n",
       "      <td>2004-06-08</td>\n",
       "      <td>640</td>\n",
       "      <td>condition_9</td>\n",
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       "    <tr>\n",
       "      <th>17280</th>\n",
       "      <td>2004-06-08 12:30:00</td>\n",
       "      <td>2004-06-08</td>\n",
       "      <td>27</td>\n",
       "      <td>condition_9</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>17281 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 timestamp        date  activity           Id\n",
       "0      2004-05-27 12:30:00  2004-05-27         5  condition_9\n",
       "1      2004-05-27 12:31:00  2004-05-27         5  condition_9\n",
       "2      2004-05-27 12:32:00  2004-05-27         5  condition_9\n",
       "3      2004-05-27 12:33:00  2004-05-27         5  condition_9\n",
       "4      2004-05-27 12:34:00  2004-05-27         5  condition_9\n",
       "...                    ...         ...       ...          ...\n",
       "17276  2004-06-08 12:26:00  2004-06-08        80  condition_9\n",
       "17277  2004-06-08 12:27:00  2004-06-08         3  condition_9\n",
       "17278  2004-06-08 12:28:00  2004-06-08        23  condition_9\n",
       "17279  2004-06-08 12:29:00  2004-06-08       640  condition_9\n",
       "17280  2004-06-08 12:30:00  2004-06-08        27  condition_9\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nine_df= pd.read_csv('condition_9.csv')\n",
    "nine_df= nine_df.drop(nine_df.index[0: 0])\n",
    "nine_df= nine_df.drop(nine_df.index[17281: 29494])\n",
    "nine_df['Id'] =np.nan\n",
    "nine_df['Id'].fillna('condition_9', inplace = True)\n",
    "nine_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp  13:00  14:00  15:00  16:00 17:00  18:00  19:00 20:00  21:00  22:00  \\\n",
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     "execution_count": 84,
     "metadata": {},
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   "source": [
    "nine_df = load_hourly_activity(nine_df)\n",
    "nine_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 10"
   ]
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  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
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       "                 timestamp        date  activity            Id\n",
       "210    2004-08-31 12:30:00  2004-08-31       709  condition_10\n",
       "211    2004-08-31 12:31:00  2004-08-31       349  condition_10\n",
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       "214    2004-08-31 12:34:00  2004-08-31       384  condition_10\n",
       "...                    ...         ...       ...           ...\n",
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       "17490  2004-09-12 12:30:00  2004-09-12       397  condition_10\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ten_df= pd.read_csv('condition_10.csv')\n",
    "ten_df= ten_df.drop(ten_df.index[0: 210])\n",
    "ten_df= ten_df.drop(ten_df.index[17281: 21656])\n",
    "ten_df['Id'] =np.nan\n",
    "ten_df['Id'].fillna('condition_10', inplace= True)\n",
    "ten_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp  13:00  14:00  15:00  16:00  17:00  18:00 19:00 20:00  21:00  22:00  \\\n",
       "0          15269  30983  29740  26452  30292  17397  7210  7103  12329  15626   \n",
       "\n",
       "timestamp  ... 04:00 05:00 06:00 07:00 08:00  09:00  10:00  11:00  12:00  Id  \n",
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     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "ten_df = load_hourly_activity(ten_df)\n",
    "ten_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
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       "                 timestamp        date  activity            Id\n",
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       "184    2004-09-28 12:34:00  2004-09-28        25  condition_11\n",
       "...                    ...         ...       ...           ...\n",
       "17456  2004-10-10 12:26:00  2004-10-10         0  condition_11\n",
       "17457  2004-10-10 12:27:00  2004-10-10         0  condition_11\n",
       "17458  2004-10-10 12:28:00  2004-10-10         0  condition_11\n",
       "17459  2004-10-10 12:29:00  2004-10-10         0  condition_11\n",
       "17460  2004-10-10 12:30:00  2004-10-10         0  condition_11\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eleven_df= pd.read_csv('condition_11.csv')\n",
    "eleven_df= eleven_df.drop(eleven_df.index[0: 180])\n",
    "eleven_df= eleven_df.drop(eleven_df.index[17281: 24773])\n",
    "eleven_df['Id'] =np.nan\n",
    "eleven_df['Id'].fillna('condition_11', inplace = True)\n",
    "eleven_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "execution_count": 90,
     "metadata": {},
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   "source": [
    "eleven_df = load_hourly_activity(eleven_df)\n",
    "eleven_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 12"
   ]
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  {
   "cell_type": "code",
   "execution_count": 93,
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       "                 timestamp        date  activity            Id\n",
       "150    2005-03-08 12:30:00  2005-03-08      2347  condition_12\n",
       "151    2005-03-08 12:31:00  2005-03-08      2918  condition_12\n",
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       "153    2005-03-08 12:33:00  2005-03-08      3103  condition_12\n",
       "154    2005-03-08 12:34:00  2005-03-08      1379  condition_12\n",
       "...                    ...         ...       ...           ...\n",
       "17426  2005-03-20 12:26:00  2005-03-20       410  condition_12\n",
       "17427  2005-03-20 12:27:00  2005-03-20       166  condition_12\n",
       "17428  2005-03-20 12:28:00  2005-03-20       149  condition_12\n",
       "17429  2005-03-20 12:29:00  2005-03-20       285  condition_12\n",
       "17430  2005-03-20 12:30:00  2005-03-20       184  condition_12\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twelve_df= pd.read_csv('condition_12.csv')\n",
    "twelve_df= twelve_df.drop(twelve_df.index[0: 150])\n",
    "twelve_df= twelve_df.drop(twelve_df.index[17281: 34638])\n",
    "twelve_df['Id'] =np.nan\n",
    "twelve_df['Id'].fillna('condition_12', inplace = True)\n",
    "twelve_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp  13:00  14:00  15:00  16:00  17:00 18:00  19:00  20:00  21:00  \\\n",
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       "\n",
       "timestamp  22:00  ... 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00  \\\n",
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       "timestamp  Id  \n",
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     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "twelve_df = load_hourly_activity(twelve_df)\n",
    "twelve_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "                 timestamp        date  activity            Id\n",
       "210    2005-08-11 12:30:00  2005-08-11      1449  condition_13\n",
       "211    2005-08-11 12:31:00  2005-08-11       904  condition_13\n",
       "212    2005-08-11 12:32:00  2005-08-11       993  condition_13\n",
       "213    2005-08-11 12:33:00  2005-08-11       822  condition_13\n",
       "214    2005-08-11 12:34:00  2005-08-11       248  condition_13\n",
       "...                    ...         ...       ...           ...\n",
       "17486  2005-08-23 12:26:00  2005-08-23       748  condition_13\n",
       "17487  2005-08-23 12:27:00  2005-08-23       796  condition_13\n",
       "17488  2005-08-23 12:28:00  2005-08-23       748  condition_13\n",
       "17489  2005-08-23 12:29:00  2005-08-23       772  condition_13\n",
       "17490  2005-08-23 12:30:00  2005-08-23       658  condition_13\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "thirteen_df= pd.read_csv('condition_13.csv')\n",
    "thirteen_df= thirteen_df.drop(thirteen_df.index[0: 210])\n",
    "thirteen_df= thirteen_df.drop(thirteen_df.index[17281: 25991])\n",
    "thirteen_df['Id'] =np.nan\n",
    "thirteen_df['Id'].fillna('condition_13', inplace= True)\n",
    "thirteen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "thirteen_df = load_hourly_activity(thirteen_df)\n",
    "thirteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 14"
   ]
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   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
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       "                 timestamp        date  activity            Id\n",
       "120    2005-08-18 12:30:00  2005-08-18       862  condition_14\n",
       "121    2005-08-18 12:31:00  2005-08-18       809  condition_14\n",
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       "...                    ...         ...       ...           ...\n",
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       "17400  2005-08-30 12:30:00  2005-08-30         0  condition_14\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fourteen_df = pd.read_csv(\"condition_14.csv\")\n",
    "fourteen_df= fourteen_df.drop(fourteen_df.index[0: 120])\n",
    "fourteen_df= fourteen_df.drop(fourteen_df.index[17281: 25991])\n",
    "fourteen_df['Id'] =np.nan\n",
    "fourteen_df['Id'].fillna('condition_14', inplace= True)\n",
    "fourteen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp  13:00 14:00  15:00 16:00 17:00  18:00 19:00 20:00 21:00 22:00  ...  \\\n",
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       "timestamp 04:00 05:00  06:00 07:00 08:00  09:00 10:00 11:00 12:00  Id  \n",
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     "execution_count": 99,
     "metadata": {},
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   "source": [
    "fourteen_df = load_hourly_activity(fourteen_df)\n",
    "fourteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
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      ],
      "text/plain": [
       "                 timestamp        date  activity            Id\n",
       "150    2005-08-30 12:30:00  2005-08-30       369  condition_15\n",
       "151    2005-08-30 12:31:00  2005-08-30       637  condition_15\n",
       "152    2005-08-30 12:32:00  2005-08-30       904  condition_15\n",
       "153    2005-08-30 12:33:00  2005-08-30       420  condition_15\n",
       "154    2005-08-30 12:34:00  2005-08-30       172  condition_15\n",
       "...                    ...         ...       ...           ...\n",
       "17426  2005-09-11 12:26:00  2005-09-11        97  condition_15\n",
       "17427  2005-09-11 12:27:00  2005-09-11        27  condition_15\n",
       "17428  2005-09-11 12:28:00  2005-09-11        61  condition_15\n",
       "17429  2005-09-11 12:29:00  2005-09-11        22  condition_15\n",
       "17430  2005-09-11 12:30:00  2005-09-11        14  condition_15\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fifteen_df = pd.read_csv(\"condition_15.csv\")\n",
    "fifteen_df= fifteen_df.drop(fifteen_df.index[0: 150])\n",
    "fifteen_df= fifteen_df.drop(fifteen_df.index[17281: 25991])\n",
    "fifteen_df['Id'] =np.nan\n",
    "fifteen_df['Id'].fillna('condition_15', inplace= True)\n",
    "fifteen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "      <td>NaN</td>\n",
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       "</table>\n",
       "<p>1 rows × 289 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp  13:00  14:00  15:00  16:00  17:00 18:00 19:00 20:00 21:00 22:00  \\\n",
       "0          12212  13468  14119  20368  14558  3216   201  2602  5469  6386   \n",
       "\n",
       "timestamp  ... 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00  12:00  Id  \n",
       "0          ...  2479   102   640   530   266   581  1063   308  11694 NaN  \n",
       "\n",
       "[1 rows x 289 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fifteen_df = load_hourly_activity(fifteen_df)\n",
    "fifteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 16"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sixteen_df = pd.read_csv(\"condition_16.csv\")\n",
    "sixteen_df= sixteen_df.drop(sixteen_df.index[0: 150])\n",
    "sixteen_df= sixteen_df.drop(sixteen_df.index[17281: 44554])\n",
    "sixteen_df['Id'] =np.nan\n",
    "sixteen_df['Id'].fillna('condition_16', inplace= True)\n",
    "sixteen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 108,
     "metadata": {},
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   "source": [
    "sixteen_df = load_hourly_activity(sixteen_df)\n",
    "sixteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 17"
   ]
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  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
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       "                 timestamp        date  activity            Id\n",
       "180    2005-11-08 12:30:00  2005-11-08         0  condition_17\n",
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       "...                    ...         ...       ...           ...\n",
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       "\n",
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     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "seventeen_df = pd.read_csv(\"condition_17.csv\")\n",
    "seventeen_df= seventeen_df.drop(seventeen_df.index[0: 180])\n",
    "seventeen_df= seventeen_df.drop(seventeen_df.index[17281: 41848])\n",
    "seventeen_df['Id'] =np.nan\n",
    "seventeen_df['Id'].fillna('condition_17', inplace= True)\n",
    "seventeen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00  Id  \n",
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     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "seventeen_df = load_hourly_activity(seventeen_df)\n",
    "seventeen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
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       "      <td>2005-11-20 12:29:00</td>\n",
       "      <td>2005-11-20</td>\n",
       "      <td>87</td>\n",
       "      <td>condition_18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17280</th>\n",
       "      <td>2005-11-20 12:30:00</td>\n",
       "      <td>2005-11-20</td>\n",
       "      <td>0</td>\n",
       "      <td>condition_18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17281 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 timestamp        date  activity            Id\n",
       "0      2005-11-08 12:30:00  2005-11-08         0  condition_18\n",
       "1      2005-11-08 12:31:00  2005-11-08         0  condition_18\n",
       "2      2005-11-08 12:32:00  2005-11-08         0  condition_18\n",
       "3      2005-11-08 12:33:00  2005-11-08         0  condition_18\n",
       "4      2005-11-08 12:34:00  2005-11-08         0  condition_18\n",
       "...                    ...         ...       ...           ...\n",
       "17276  2005-11-20 12:26:00  2005-11-20       120  condition_18\n",
       "17277  2005-11-20 12:27:00  2005-11-20       158  condition_18\n",
       "17278  2005-11-20 12:28:00  2005-11-20       174  condition_18\n",
       "17279  2005-11-20 12:29:00  2005-11-20        87  condition_18\n",
       "17280  2005-11-20 12:30:00  2005-11-20         0  condition_18\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eighteen_df = pd.read_csv(\"condition_18.csv\")\n",
    "eighteen_df= eighteen_df.drop(eighteen_df.index[0: 0])\n",
    "eighteen_df= eighteen_df.drop(eighteen_df.index[17281: 41848])\n",
    "eighteen_df['Id'] =np.nan\n",
    "eighteen_df['Id'].fillna('condition_18', inplace= True)\n",
    "eighteen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00  ...  \\\n",
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       "timestamp 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00  12:00  Id  \n",
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     "execution_count": 112,
     "metadata": {},
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   "source": [
    "eighteen_df = load_hourly_activity(eighteen_df)\n",
    "eighteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 19"
   ]
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  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
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       "                 timestamp        date  activity            Id\n",
       "1320   2002-08-30 12:30:00  2002-08-30       223  condition_19\n",
       "1321   2002-08-30 12:31:00  2002-08-30       336  condition_19\n",
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       "1323   2002-08-30 12:33:00  2002-08-30       424  condition_19\n",
       "1324   2002-08-30 12:34:00  2002-08-30       666  condition_19\n",
       "...                    ...         ...       ...           ...\n",
       "18596  2002-09-11 12:26:00  2002-09-11       249  condition_19\n",
       "18597  2002-09-11 12:27:00  2002-09-11       111  condition_19\n",
       "18598  2002-09-11 12:28:00  2002-09-11       216  condition_19\n",
       "18599  2002-09-11 12:29:00  2002-09-11        48  condition_19\n",
       "18600  2002-09-11 12:30:00  2002-09-11       336  condition_19\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nineteen_df = pd.read_csv(\"condition_19.csv\")\n",
    "nineteen_df= nineteen_df.drop(nineteen_df.index[0: 1320])\n",
    "nineteen_df= nineteen_df.drop(nineteen_df.index[17281: 41848])\n",
    "nineteen_df['Id'] =np.nan\n",
    "nineteen_df['Id'].fillna('condition_19', inplace= True)\n",
    "nineteen_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
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      ],
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       "timestamp  13:00  14:00  15:00  16:00 17:00  18:00 19:00 20:00 21:00 22:00  \\\n",
       "0          19917  28442  19867  12910  7818  10029  9269  7009  7239  2955   \n",
       "\n",
       "timestamp  ... 04:00 05:00 06:00 07:00 08:00  09:00  10:00  11:00  12:00  Id  \n",
       "0          ...   315   343   422  7204  8194  11864  15835  25036  15167 NaN  \n",
       "\n",
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     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nineteen_df = load_hourly_activity(nineteen_df)\n",
    "nineteen_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
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       "                 timestamp        date  activity          Id\n",
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       "...                    ...         ...       ...         ...\n",
       "17486  2004-02-08 12:26:00  2004-02-08       550  control_20\n",
       "17487  2004-02-08 12:27:00  2004-02-08        46  control_20\n",
       "17488  2004-02-08 12:28:00  2004-02-08         0  control_20\n",
       "17489  2004-02-08 12:29:00  2004-02-08        29  control_20\n",
       "17490  2004-02-08 12:30:00  2004-02-08         3  control_20\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twenty_df = pd.read_csv(\"control_20.csv\")\n",
    "twenty_df= twenty_df.drop(twenty_df.index[0: 210])\n",
    "twenty_df= twenty_df.drop(twenty_df.index[17281: 41848])\n",
    "twenty_df['Id'] =np.nan\n",
    "twenty_df['Id'].fillna('control_20', inplace= True)\n",
    "twenty_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 117,
     "metadata": {},
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   "source": [
    "twenty_df = load_hourly_activity(twenty_df)\n",
    "twenty_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 21"
   ]
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   "cell_type": "code",
   "execution_count": 120,
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       "                 timestamp        date  activity            Id\n",
       "1375   2002-06-14 12:30:00  2002-06-14         0  condition_21\n",
       "1376   2002-06-14 12:31:00  2002-06-14         0  condition_21\n",
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       "1379   2002-06-14 12:34:00  2002-06-14         0  condition_21\n",
       "...                    ...         ...       ...           ...\n",
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       "18655  2002-06-26 12:30:00  2002-06-26       235  condition_21\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twentyone_df = pd.read_csv(\"condition_21.csv\")\n",
    "twentyone_df= twentyone_df.drop(twentyone_df.index[0: 1375])\n",
    "twentyone_df= twentyone_df.drop(twentyone_df.index[17281: 41848])\n",
    "twentyone_df['Id'] =np.nan\n",
    "twentyone_df['Id'].fillna('condition_21', inplace= True)\n",
    "twentyone_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp 13:00 14:00  15:00 16:00 17:00 18:00 19:00  20:00 21:00 22:00  ...  \\\n",
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       "timestamp 04:00 05:00 06:00 07:00 08:00 09:00 10:00  11:00  12:00  Id  \n",
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     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "twentyone_df = load_hourly_activity(twentyone_df)\n",
    "twentyone_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "                 timestamp        date  activity            Id\n",
       "105    2002-11-05 12:30:00  2002-11-05       152  condition_22\n",
       "106    2002-11-05 12:31:00  2002-11-05       360  condition_22\n",
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       "108    2002-11-05 12:33:00  2002-11-05       216  condition_22\n",
       "109    2002-11-05 12:34:00  2002-11-05       384  condition_22\n",
       "...                    ...         ...       ...           ...\n",
       "17381  2002-11-17 12:26:00  2002-11-17       348  condition_22\n",
       "17382  2002-11-17 12:27:00  2002-11-17       304  condition_22\n",
       "17383  2002-11-17 12:28:00  2002-11-17       733  condition_22\n",
       "17384  2002-11-17 12:29:00  2002-11-17       266  condition_22\n",
       "17385  2002-11-17 12:30:00  2002-11-17       216  condition_22\n",
       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twentytwo_df = pd.read_csv(\"condition_22.csv\")\n",
    "twentytwo_df= twentytwo_df.drop(twentytwo_df.index[0: 105])\n",
    "twentytwo_df= twentytwo_df.drop(twentytwo_df.index[17281: 41848])\n",
    "twentytwo_df['Id'] =np.nan\n",
    "twentytwo_df['Id'].fillna('condition_22', inplace= True)\n",
    "twentytwo_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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       "timestamp 13:00 14:00  15:00  16:00  17:00  18:00  19:00  20:00  21:00  22:00  \\\n",
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     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "twentytwo_df = load_hourly_activity(twentytwo_df)\n",
    "twentytwo_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 23"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
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       "                 timestamp        date  activity            Id\n",
       "1410   2002-06-07 12:30:00  2002-06-07       394  condition_23\n",
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       "...                    ...         ...       ...           ...\n",
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       "\n",
       "[17281 rows x 4 columns]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twentythree_df = pd.read_csv(\"condition_23.csv\")\n",
    "twentythree_df= twentythree_df.drop(twentythree_df.index[0: 1410])\n",
    "twentythree_df= twentythree_df.drop(twentythree_df.index[17281: 41848])\n",
    "twentythree_df['Id'] =np.nan\n",
    "twentythree_df['Id'].fillna('condition_23', inplace= True)\n",
    "twentythree_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-9fa85ab700bc>:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  frame['total_hour_activity'] = list\n",
      "c:\\users\\philip agbo\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\pandas\\core\\series.py:4517: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
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     "execution_count": 129,
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   "source": [
    "twentythree_df= load_hourly_activity(twentythree_df)\n",
    "twentythree_df"
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  {
   "cell_type": "code",
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       "      <td>24753</td>\n",
       "      <td>20679</td>\n",
       "      <td>924</td>\n",
       "      <td>229</td>\n",
       "      <td>13181</td>\n",
       "      <td>16471</td>\n",
       "      <td>14487</td>\n",
       "      <td>12526</td>\n",
       "      <td>12723</td>\n",
       "      <td>...</td>\n",
       "      <td>13988</td>\n",
       "      <td>736</td>\n",
       "      <td>682</td>\n",
       "      <td>539</td>\n",
       "      <td>475</td>\n",
       "      <td>545</td>\n",
       "      <td>1306</td>\n",
       "      <td>616</td>\n",
       "      <td>10203</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17396</td>\n",
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       "      <td>4221</td>\n",
       "      <td>13189</td>\n",
       "      <td>36219</td>\n",
       "      <td>7854</td>\n",
       "      <td>...</td>\n",
       "      <td>340</td>\n",
       "      <td>180</td>\n",
       "      <td>180</td>\n",
       "      <td>200</td>\n",
       "      <td>300</td>\n",
       "      <td>300</td>\n",
       "      <td>260</td>\n",
       "      <td>180</td>\n",
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       "      <td>5577</td>\n",
       "      <td>31001</td>\n",
       "      <td>18265</td>\n",
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       "      <td>1733</td>\n",
       "      <td>939</td>\n",
       "      <td>831</td>\n",
       "      <td>10754</td>\n",
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       "      <td>12533</td>\n",
       "      <td>23551</td>\n",
       "      <td>21186</td>\n",
       "      <td>26484</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15269</td>\n",
       "      <td>30983</td>\n",
       "      <td>29740</td>\n",
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       "      <td>30292</td>\n",
       "      <td>17397</td>\n",
       "      <td>7210</td>\n",
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       "      <td>988</td>\n",
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       "      <td>4927</td>\n",
       "      <td>21820</td>\n",
       "      <td>20262</td>\n",
       "      <td>42449</td>\n",
       "      <td>35300</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29278</td>\n",
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       "      <td>753</td>\n",
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       "      <td>1269</td>\n",
       "      <td>23656</td>\n",
       "      <td>...</td>\n",
       "      <td>4442</td>\n",
       "      <td>4924</td>\n",
       "      <td>339</td>\n",
       "      <td>292</td>\n",
       "      <td>171</td>\n",
       "      <td>53</td>\n",
       "      <td>114</td>\n",
       "      <td>219</td>\n",
       "      <td>138</td>\n",
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       "    <tr>\n",
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       "      <td>...</td>\n",
       "      <td>253</td>\n",
       "      <td>245</td>\n",
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       "      <td>1408</td>\n",
       "      <td>263</td>\n",
       "      <td>758</td>\n",
       "      <td>439</td>\n",
       "      <td>4158</td>\n",
       "      <td>7671</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>20585</td>\n",
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       "      <td>25075</td>\n",
       "      <td>29275</td>\n",
       "      <td>28359</td>\n",
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       "      <td>18589</td>\n",
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       "      <td>21111</td>\n",
       "      <td>7600</td>\n",
       "      <td>8068</td>\n",
       "      <td>13445</td>\n",
       "      <td>9408</td>\n",
       "      <td>2439</td>\n",
       "      <td>5621</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12212</td>\n",
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       "      <td>201</td>\n",
       "      <td>2602</td>\n",
       "      <td>5469</td>\n",
       "      <td>6386</td>\n",
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       "      <td>2479</td>\n",
       "      <td>102</td>\n",
       "      <td>640</td>\n",
       "      <td>530</td>\n",
       "      <td>266</td>\n",
       "      <td>581</td>\n",
       "      <td>1063</td>\n",
       "      <td>308</td>\n",
       "      <td>11694</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7903</td>\n",
       "      <td>33460</td>\n",
       "      <td>27786</td>\n",
       "      <td>22705</td>\n",
       "      <td>14429</td>\n",
       "      <td>4687</td>\n",
       "      <td>22330</td>\n",
       "      <td>10001</td>\n",
       "      <td>5265</td>\n",
       "      <td>2213</td>\n",
       "      <td>...</td>\n",
       "      <td>392</td>\n",
       "      <td>394</td>\n",
       "      <td>262</td>\n",
       "      <td>183</td>\n",
       "      <td>1578</td>\n",
       "      <td>9124</td>\n",
       "      <td>8210</td>\n",
       "      <td>62775</td>\n",
       "      <td>18306</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3981</td>\n",
       "      <td>9476</td>\n",
       "      <td>9403</td>\n",
       "      <td>8488</td>\n",
       "      <td>1713</td>\n",
       "      <td>9661</td>\n",
       "      <td>9030</td>\n",
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       "      <td>4920</td>\n",
       "      <td>4457</td>\n",
       "      <td>...</td>\n",
       "      <td>264</td>\n",
       "      <td>719</td>\n",
       "      <td>366</td>\n",
       "      <td>576</td>\n",
       "      <td>194</td>\n",
       "      <td>449</td>\n",
       "      <td>569</td>\n",
       "      <td>1188</td>\n",
       "      <td>478</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5184</td>\n",
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       "      <td>821</td>\n",
       "      <td>2379</td>\n",
       "      <td>5261</td>\n",
       "      <td>6716</td>\n",
       "      <td>4946</td>\n",
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       "      <td>4336</td>\n",
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       "      <td>2072</td>\n",
       "      <td>46</td>\n",
       "      <td>1086</td>\n",
       "      <td>455</td>\n",
       "      <td>382</td>\n",
       "      <td>4400</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19917</td>\n",
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       "      <td>10029</td>\n",
       "      <td>9269</td>\n",
       "      <td>7009</td>\n",
       "      <td>7239</td>\n",
       "      <td>2955</td>\n",
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       "      <td>315</td>\n",
       "      <td>343</td>\n",
       "      <td>422</td>\n",
       "      <td>7204</td>\n",
       "      <td>8194</td>\n",
       "      <td>11864</td>\n",
       "      <td>15835</td>\n",
       "      <td>25036</td>\n",
       "      <td>15167</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1784</td>\n",
       "      <td>26144</td>\n",
       "      <td>48610</td>\n",
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       "      <td>42044</td>\n",
       "      <td>34624</td>\n",
       "      <td>25015</td>\n",
       "      <td>30188</td>\n",
       "      <td>18576</td>\n",
       "      <td>16772</td>\n",
       "      <td>...</td>\n",
       "      <td>309</td>\n",
       "      <td>670</td>\n",
       "      <td>838</td>\n",
       "      <td>6237</td>\n",
       "      <td>12960</td>\n",
       "      <td>19177</td>\n",
       "      <td>41507</td>\n",
       "      <td>25706</td>\n",
       "      <td>35735</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2324</td>\n",
       "      <td>26545</td>\n",
       "      <td>458</td>\n",
       "      <td>296</td>\n",
       "      <td>396</td>\n",
       "      <td>721</td>\n",
       "      <td>10927</td>\n",
       "      <td>390</td>\n",
       "      <td>1838</td>\n",
       "      <td>...</td>\n",
       "      <td>518</td>\n",
       "      <td>131</td>\n",
       "      <td>350</td>\n",
       "      <td>131</td>\n",
       "      <td>520</td>\n",
       "      <td>436</td>\n",
       "      <td>494</td>\n",
       "      <td>20677</td>\n",
       "      <td>14188</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4475</td>\n",
       "      <td>9879</td>\n",
       "      <td>19711</td>\n",
       "      <td>21423</td>\n",
       "      <td>13701</td>\n",
       "      <td>20150</td>\n",
       "      <td>19552</td>\n",
       "      <td>18239</td>\n",
       "      <td>14322</td>\n",
       "      <td>16013</td>\n",
       "      <td>...</td>\n",
       "      <td>5843</td>\n",
       "      <td>97</td>\n",
       "      <td>386</td>\n",
       "      <td>1011</td>\n",
       "      <td>538</td>\n",
       "      <td>1235</td>\n",
       "      <td>30115</td>\n",
       "      <td>22752</td>\n",
       "      <td>13241</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16737</td>\n",
       "      <td>27766</td>\n",
       "      <td>42622</td>\n",
       "      <td>16658</td>\n",
       "      <td>388</td>\n",
       "      <td>562</td>\n",
       "      <td>24221</td>\n",
       "      <td>24274</td>\n",
       "      <td>12866</td>\n",
       "      <td>12158</td>\n",
       "      <td>...</td>\n",
       "      <td>2687</td>\n",
       "      <td>958</td>\n",
       "      <td>2510</td>\n",
       "      <td>339</td>\n",
       "      <td>1548</td>\n",
       "      <td>1965</td>\n",
       "      <td>609</td>\n",
       "      <td>12466</td>\n",
       "      <td>13853</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 289 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp  13:00  14:00  15:00  16:00  17:00  18:00  19:00  20:00  21:00  \\\n",
       "0          10971  17074  16751  13127  14313  12591   7747   3628   5997   \n",
       "0          12092  30845  23816  29557  23204  15980   9892   8865   2279   \n",
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       "0              0   5362  27889  26901  21305  23969  17600  27401  28230   \n",
       "0           8846  24753  20679    924    229  13181  16471  14487  12526   \n",
       "0          17396  18346  13312  46736  37032  24093   4221  13189  36219   \n",
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       "0          29278  11190   9113  12873    635   1208    753   4645   1269   \n",
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       "0          13101  20585  13030  18174  25075  29275  28359  20768  23365   \n",
       "0          24065   4405  13715   6910     85  12299   6713   1607   3959   \n",
       "0          12212  13468  14119  20368  14558   3216    201   2602   5469   \n",
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       "0           5184   9186   7809   6898    821   2379   5261   6716   4946   \n",
       "0          19917  28442  19867  12910   7818  10029   9269   7009   7239   \n",
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       "0              0   2324  26545    458    296    396    721  10927    390   \n",
       "0           4475   9879  19711  21423  13701  20150  19552  18239  14322   \n",
       "0          16737  27766  42622  16658    388    562  24221  24274  12866   \n",
       "\n",
       "timestamp  22:00  ...  04:00  05:00  06:00  07:00  08:00  09:00  10:00  11:00  \\\n",
       "0           2492  ...    253    415   1053    708   1519  13420  11455  13541   \n",
       "0          24152  ...    642   7899   8471  33131  32482  31988  34359  54507   \n",
       "0          33566  ...    393    653    917   4549    396   1104   1029   1757   \n",
       "0          17316  ...   9867  22773  11512     66    112     57     91    546   \n",
       "0           2548  ...     62    434    306   2495    484   9961   6422   9288   \n",
       "0          49243  ...    100    729    855    402    348   4888   7034  16314   \n",
       "0          12723  ...  13988    736    682    539    475    545   1306    616   \n",
       "0           7854  ...    340    180    180    200    300    300    260    180   \n",
       "0          18265  ...   1733    939    831  10754   1784  12533  23551  21186   \n",
       "0          15626  ...   1075   1087    988   4860   4927  21820  20262  42449   \n",
       "0          23656  ...   4442   4924    339    292    171     53    114    219   \n",
       "0          31941  ...    253    245   1712   1408    263    758    439   4158   \n",
       "0          18589  ...   1728    155    931    344   1547  18408  54268  35413   \n",
       "0              0  ...   4634   4025  21111   7600   8068  13445   9408   2439   \n",
       "0           6386  ...   2479    102    640    530    266    581   1063    308   \n",
       "0           2213  ...    392    394    262    183   1578   9124   8210  62775   \n",
       "0           4457  ...    264    719    366    576    194    449    569   1188   \n",
       "0           8674  ...   4336   2965   2072     46   1086    455    382   4400   \n",
       "0           2955  ...    315    343    422   7204   8194  11864  15835  25036   \n",
       "0          16772  ...    309    670    838   6237  12960  19177  41507  25706   \n",
       "0           1838  ...    518    131    350    131    520    436    494  20677   \n",
       "0          16013  ...   5843     97    386   1011    538   1235  30115  22752   \n",
       "0          12158  ...   2687    958   2510    339   1548   1965    609  12466   \n",
       "\n",
       "timestamp  12:00  Id  \n",
       "0          21750 NaN  \n",
       "0          22821 NaN  \n",
       "0           6388 NaN  \n",
       "0           8313 NaN  \n",
       "0          20272 NaN  \n",
       "0          25545 NaN  \n",
       "0          10203 NaN  \n",
       "0            180 NaN  \n",
       "0          26484 NaN  \n",
       "0          35300 NaN  \n",
       "0            138 NaN  \n",
       "0           7671 NaN  \n",
       "0          38573 NaN  \n",
       "0           5621 NaN  \n",
       "0          11694 NaN  \n",
       "0          18306 NaN  \n",
       "0            478 NaN  \n",
       "0          12245 NaN  \n",
       "0          15167 NaN  \n",
       "0          35735 NaN  \n",
       "0          14188 NaN  \n",
       "0          13241 NaN  \n",
       "0          13853 NaN  \n",
       "\n",
       "[23 rows x 289 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_frames = [one_df,two_df, three_df, four_df, five_df, six_df, seven_df, eight_df, nine_df, ten_df, eleven_df, twelve_df, thirteen_df,\n",
    "             fourteen_df, fifteen_df, sixteen_df, seventeen_df, eighteen_df, nineteen_df, twenty_df, twentyone_df, twentytwo_df,\n",
    "             twentythree_df]\n",
    "condition_df = pd.concat(all_frames)\n",
    "condition_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>timestamp</th>\n",
       "      <th>13:00</th>\n",
       "      <th>14:00</th>\n",
       "      <th>15:00</th>\n",
       "      <th>16:00</th>\n",
       "      <th>17:00</th>\n",
       "      <th>18:00</th>\n",
       "      <th>19:00</th>\n",
       "      <th>20:00</th>\n",
       "      <th>21:00</th>\n",
       "      <th>22:00</th>\n",
       "      <th>...</th>\n",
       "      <th>03:00</th>\n",
       "      <th>04:00</th>\n",
       "      <th>05:00</th>\n",
       "      <th>06:00</th>\n",
       "      <th>07:00</th>\n",
       "      <th>08:00</th>\n",
       "      <th>09:00</th>\n",
       "      <th>10:00</th>\n",
       "      <th>11:00</th>\n",
       "      <th>12:00</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10971</td>\n",
       "      <td>17074</td>\n",
       "      <td>16751</td>\n",
       "      <td>13127</td>\n",
       "      <td>14313</td>\n",
       "      <td>12591</td>\n",
       "      <td>7747</td>\n",
       "      <td>3628</td>\n",
       "      <td>5997</td>\n",
       "      <td>2492</td>\n",
       "      <td>...</td>\n",
       "      <td>295</td>\n",
       "      <td>253</td>\n",
       "      <td>415</td>\n",
       "      <td>1053</td>\n",
       "      <td>708</td>\n",
       "      <td>1519</td>\n",
       "      <td>13420</td>\n",
       "      <td>11455</td>\n",
       "      <td>13541</td>\n",
       "      <td>21750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12092</td>\n",
       "      <td>30845</td>\n",
       "      <td>23816</td>\n",
       "      <td>29557</td>\n",
       "      <td>23204</td>\n",
       "      <td>15980</td>\n",
       "      <td>9892</td>\n",
       "      <td>8865</td>\n",
       "      <td>2279</td>\n",
       "      <td>24152</td>\n",
       "      <td>...</td>\n",
       "      <td>1115</td>\n",
       "      <td>642</td>\n",
       "      <td>7899</td>\n",
       "      <td>8471</td>\n",
       "      <td>33131</td>\n",
       "      <td>32482</td>\n",
       "      <td>31988</td>\n",
       "      <td>34359</td>\n",
       "      <td>54507</td>\n",
       "      <td>22821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5766</td>\n",
       "      <td>23582</td>\n",
       "      <td>26507</td>\n",
       "      <td>62600</td>\n",
       "      <td>36530</td>\n",
       "      <td>40782</td>\n",
       "      <td>19567</td>\n",
       "      <td>10192</td>\n",
       "      <td>19797</td>\n",
       "      <td>33566</td>\n",
       "      <td>...</td>\n",
       "      <td>8587</td>\n",
       "      <td>393</td>\n",
       "      <td>653</td>\n",
       "      <td>917</td>\n",
       "      <td>4549</td>\n",
       "      <td>396</td>\n",
       "      <td>1104</td>\n",
       "      <td>1029</td>\n",
       "      <td>1757</td>\n",
       "      <td>6388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6024</td>\n",
       "      <td>12516</td>\n",
       "      <td>19457</td>\n",
       "      <td>11004</td>\n",
       "      <td>15760</td>\n",
       "      <td>9629</td>\n",
       "      <td>9633</td>\n",
       "      <td>10585</td>\n",
       "      <td>14169</td>\n",
       "      <td>17316</td>\n",
       "      <td>...</td>\n",
       "      <td>21922</td>\n",
       "      <td>9867</td>\n",
       "      <td>22773</td>\n",
       "      <td>11512</td>\n",
       "      <td>66</td>\n",
       "      <td>112</td>\n",
       "      <td>57</td>\n",
       "      <td>91</td>\n",
       "      <td>546</td>\n",
       "      <td>8313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15950</td>\n",
       "      <td>17506</td>\n",
       "      <td>17953</td>\n",
       "      <td>7259</td>\n",
       "      <td>9337</td>\n",
       "      <td>838</td>\n",
       "      <td>6650</td>\n",
       "      <td>6212</td>\n",
       "      <td>5160</td>\n",
       "      <td>2548</td>\n",
       "      <td>...</td>\n",
       "      <td>602</td>\n",
       "      <td>62</td>\n",
       "      <td>434</td>\n",
       "      <td>306</td>\n",
       "      <td>2495</td>\n",
       "      <td>484</td>\n",
       "      <td>9961</td>\n",
       "      <td>6422</td>\n",
       "      <td>9288</td>\n",
       "      <td>20272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>5362</td>\n",
       "      <td>27889</td>\n",
       "      <td>26901</td>\n",
       "      <td>21305</td>\n",
       "      <td>23969</td>\n",
       "      <td>17600</td>\n",
       "      <td>27401</td>\n",
       "      <td>28230</td>\n",
       "      <td>49243</td>\n",
       "      <td>...</td>\n",
       "      <td>2050</td>\n",
       "      <td>100</td>\n",
       "      <td>729</td>\n",
       "      <td>855</td>\n",
       "      <td>402</td>\n",
       "      <td>348</td>\n",
       "      <td>4888</td>\n",
       "      <td>7034</td>\n",
       "      <td>16314</td>\n",
       "      <td>25545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8846</td>\n",
       "      <td>24753</td>\n",
       "      <td>20679</td>\n",
       "      <td>924</td>\n",
       "      <td>229</td>\n",
       "      <td>13181</td>\n",
       "      <td>16471</td>\n",
       "      <td>14487</td>\n",
       "      <td>12526</td>\n",
       "      <td>12723</td>\n",
       "      <td>...</td>\n",
       "      <td>9542</td>\n",
       "      <td>13988</td>\n",
       "      <td>736</td>\n",
       "      <td>682</td>\n",
       "      <td>539</td>\n",
       "      <td>475</td>\n",
       "      <td>545</td>\n",
       "      <td>1306</td>\n",
       "      <td>616</td>\n",
       "      <td>10203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17396</td>\n",
       "      <td>18346</td>\n",
       "      <td>13312</td>\n",
       "      <td>46736</td>\n",
       "      <td>37032</td>\n",
       "      <td>24093</td>\n",
       "      <td>4221</td>\n",
       "      <td>13189</td>\n",
       "      <td>36219</td>\n",
       "      <td>7854</td>\n",
       "      <td>...</td>\n",
       "      <td>180</td>\n",
       "      <td>340</td>\n",
       "      <td>180</td>\n",
       "      <td>180</td>\n",
       "      <td>200</td>\n",
       "      <td>300</td>\n",
       "      <td>300</td>\n",
       "      <td>260</td>\n",
       "      <td>180</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>25829</td>\n",
       "      <td>38170</td>\n",
       "      <td>21443</td>\n",
       "      <td>13205</td>\n",
       "      <td>8028</td>\n",
       "      <td>20502</td>\n",
       "      <td>15481</td>\n",
       "      <td>5577</td>\n",
       "      <td>31001</td>\n",
       "      <td>18265</td>\n",
       "      <td>...</td>\n",
       "      <td>509</td>\n",
       "      <td>1733</td>\n",
       "      <td>939</td>\n",
       "      <td>831</td>\n",
       "      <td>10754</td>\n",
       "      <td>1784</td>\n",
       "      <td>12533</td>\n",
       "      <td>23551</td>\n",
       "      <td>21186</td>\n",
       "      <td>26484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15269</td>\n",
       "      <td>30983</td>\n",
       "      <td>29740</td>\n",
       "      <td>26452</td>\n",
       "      <td>30292</td>\n",
       "      <td>17397</td>\n",
       "      <td>7210</td>\n",
       "      <td>7103</td>\n",
       "      <td>12329</td>\n",
       "      <td>15626</td>\n",
       "      <td>...</td>\n",
       "      <td>1586</td>\n",
       "      <td>1075</td>\n",
       "      <td>1087</td>\n",
       "      <td>988</td>\n",
       "      <td>4860</td>\n",
       "      <td>4927</td>\n",
       "      <td>21820</td>\n",
       "      <td>20262</td>\n",
       "      <td>42449</td>\n",
       "      <td>35300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29278</td>\n",
       "      <td>11190</td>\n",
       "      <td>9113</td>\n",
       "      <td>12873</td>\n",
       "      <td>635</td>\n",
       "      <td>1208</td>\n",
       "      <td>753</td>\n",
       "      <td>4645</td>\n",
       "      <td>1269</td>\n",
       "      <td>23656</td>\n",
       "      <td>...</td>\n",
       "      <td>2499</td>\n",
       "      <td>4442</td>\n",
       "      <td>4924</td>\n",
       "      <td>339</td>\n",
       "      <td>292</td>\n",
       "      <td>171</td>\n",
       "      <td>53</td>\n",
       "      <td>114</td>\n",
       "      <td>219</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36873</td>\n",
       "      <td>29568</td>\n",
       "      <td>18006</td>\n",
       "      <td>35299</td>\n",
       "      <td>10799</td>\n",
       "      <td>2109</td>\n",
       "      <td>24114</td>\n",
       "      <td>15290</td>\n",
       "      <td>13781</td>\n",
       "      <td>31941</td>\n",
       "      <td>...</td>\n",
       "      <td>847</td>\n",
       "      <td>253</td>\n",
       "      <td>245</td>\n",
       "      <td>1712</td>\n",
       "      <td>1408</td>\n",
       "      <td>263</td>\n",
       "      <td>758</td>\n",
       "      <td>439</td>\n",
       "      <td>4158</td>\n",
       "      <td>7671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13101</td>\n",
       "      <td>20585</td>\n",
       "      <td>13030</td>\n",
       "      <td>18174</td>\n",
       "      <td>25075</td>\n",
       "      <td>29275</td>\n",
       "      <td>28359</td>\n",
       "      <td>20768</td>\n",
       "      <td>23365</td>\n",
       "      <td>18589</td>\n",
       "      <td>...</td>\n",
       "      <td>152</td>\n",
       "      <td>1728</td>\n",
       "      <td>155</td>\n",
       "      <td>931</td>\n",
       "      <td>344</td>\n",
       "      <td>1547</td>\n",
       "      <td>18408</td>\n",
       "      <td>54268</td>\n",
       "      <td>35413</td>\n",
       "      <td>38573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24065</td>\n",
       "      <td>4405</td>\n",
       "      <td>13715</td>\n",
       "      <td>6910</td>\n",
       "      <td>85</td>\n",
       "      <td>12299</td>\n",
       "      <td>6713</td>\n",
       "      <td>1607</td>\n",
       "      <td>3959</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>11894</td>\n",
       "      <td>4634</td>\n",
       "      <td>4025</td>\n",
       "      <td>21111</td>\n",
       "      <td>7600</td>\n",
       "      <td>8068</td>\n",
       "      <td>13445</td>\n",
       "      <td>9408</td>\n",
       "      <td>2439</td>\n",
       "      <td>5621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12212</td>\n",
       "      <td>13468</td>\n",
       "      <td>14119</td>\n",
       "      <td>20368</td>\n",
       "      <td>14558</td>\n",
       "      <td>3216</td>\n",
       "      <td>201</td>\n",
       "      <td>2602</td>\n",
       "      <td>5469</td>\n",
       "      <td>6386</td>\n",
       "      <td>...</td>\n",
       "      <td>3983</td>\n",
       "      <td>2479</td>\n",
       "      <td>102</td>\n",
       "      <td>640</td>\n",
       "      <td>530</td>\n",
       "      <td>266</td>\n",
       "      <td>581</td>\n",
       "      <td>1063</td>\n",
       "      <td>308</td>\n",
       "      <td>11694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7903</td>\n",
       "      <td>33460</td>\n",
       "      <td>27786</td>\n",
       "      <td>22705</td>\n",
       "      <td>14429</td>\n",
       "      <td>4687</td>\n",
       "      <td>22330</td>\n",
       "      <td>10001</td>\n",
       "      <td>5265</td>\n",
       "      <td>2213</td>\n",
       "      <td>...</td>\n",
       "      <td>401</td>\n",
       "      <td>392</td>\n",
       "      <td>394</td>\n",
       "      <td>262</td>\n",
       "      <td>183</td>\n",
       "      <td>1578</td>\n",
       "      <td>9124</td>\n",
       "      <td>8210</td>\n",
       "      <td>62775</td>\n",
       "      <td>18306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3981</td>\n",
       "      <td>9476</td>\n",
       "      <td>9403</td>\n",
       "      <td>8488</td>\n",
       "      <td>1713</td>\n",
       "      <td>9661</td>\n",
       "      <td>9030</td>\n",
       "      <td>5152</td>\n",
       "      <td>4920</td>\n",
       "      <td>4457</td>\n",
       "      <td>...</td>\n",
       "      <td>781</td>\n",
       "      <td>264</td>\n",
       "      <td>719</td>\n",
       "      <td>366</td>\n",
       "      <td>576</td>\n",
       "      <td>194</td>\n",
       "      <td>449</td>\n",
       "      <td>569</td>\n",
       "      <td>1188</td>\n",
       "      <td>478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5184</td>\n",
       "      <td>9186</td>\n",
       "      <td>7809</td>\n",
       "      <td>6898</td>\n",
       "      <td>821</td>\n",
       "      <td>2379</td>\n",
       "      <td>5261</td>\n",
       "      <td>6716</td>\n",
       "      <td>4946</td>\n",
       "      <td>8674</td>\n",
       "      <td>...</td>\n",
       "      <td>2843</td>\n",
       "      <td>4336</td>\n",
       "      <td>2965</td>\n",
       "      <td>2072</td>\n",
       "      <td>46</td>\n",
       "      <td>1086</td>\n",
       "      <td>455</td>\n",
       "      <td>382</td>\n",
       "      <td>4400</td>\n",
       "      <td>12245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19917</td>\n",
       "      <td>28442</td>\n",
       "      <td>19867</td>\n",
       "      <td>12910</td>\n",
       "      <td>7818</td>\n",
       "      <td>10029</td>\n",
       "      <td>9269</td>\n",
       "      <td>7009</td>\n",
       "      <td>7239</td>\n",
       "      <td>2955</td>\n",
       "      <td>...</td>\n",
       "      <td>503</td>\n",
       "      <td>315</td>\n",
       "      <td>343</td>\n",
       "      <td>422</td>\n",
       "      <td>7204</td>\n",
       "      <td>8194</td>\n",
       "      <td>11864</td>\n",
       "      <td>15835</td>\n",
       "      <td>25036</td>\n",
       "      <td>15167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1784</td>\n",
       "      <td>26144</td>\n",
       "      <td>48610</td>\n",
       "      <td>32403</td>\n",
       "      <td>42044</td>\n",
       "      <td>34624</td>\n",
       "      <td>25015</td>\n",
       "      <td>30188</td>\n",
       "      <td>18576</td>\n",
       "      <td>16772</td>\n",
       "      <td>...</td>\n",
       "      <td>302</td>\n",
       "      <td>309</td>\n",
       "      <td>670</td>\n",
       "      <td>838</td>\n",
       "      <td>6237</td>\n",
       "      <td>12960</td>\n",
       "      <td>19177</td>\n",
       "      <td>41507</td>\n",
       "      <td>25706</td>\n",
       "      <td>35735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2324</td>\n",
       "      <td>26545</td>\n",
       "      <td>458</td>\n",
       "      <td>296</td>\n",
       "      <td>396</td>\n",
       "      <td>721</td>\n",
       "      <td>10927</td>\n",
       "      <td>390</td>\n",
       "      <td>1838</td>\n",
       "      <td>...</td>\n",
       "      <td>423</td>\n",
       "      <td>518</td>\n",
       "      <td>131</td>\n",
       "      <td>350</td>\n",
       "      <td>131</td>\n",
       "      <td>520</td>\n",
       "      <td>436</td>\n",
       "      <td>494</td>\n",
       "      <td>20677</td>\n",
       "      <td>14188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4475</td>\n",
       "      <td>9879</td>\n",
       "      <td>19711</td>\n",
       "      <td>21423</td>\n",
       "      <td>13701</td>\n",
       "      <td>20150</td>\n",
       "      <td>19552</td>\n",
       "      <td>18239</td>\n",
       "      <td>14322</td>\n",
       "      <td>16013</td>\n",
       "      <td>...</td>\n",
       "      <td>139</td>\n",
       "      <td>5843</td>\n",
       "      <td>97</td>\n",
       "      <td>386</td>\n",
       "      <td>1011</td>\n",
       "      <td>538</td>\n",
       "      <td>1235</td>\n",
       "      <td>30115</td>\n",
       "      <td>22752</td>\n",
       "      <td>13241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16737</td>\n",
       "      <td>27766</td>\n",
       "      <td>42622</td>\n",
       "      <td>16658</td>\n",
       "      <td>388</td>\n",
       "      <td>562</td>\n",
       "      <td>24221</td>\n",
       "      <td>24274</td>\n",
       "      <td>12866</td>\n",
       "      <td>12158</td>\n",
       "      <td>...</td>\n",
       "      <td>1105</td>\n",
       "      <td>2687</td>\n",
       "      <td>958</td>\n",
       "      <td>2510</td>\n",
       "      <td>339</td>\n",
       "      <td>1548</td>\n",
       "      <td>1965</td>\n",
       "      <td>609</td>\n",
       "      <td>12466</td>\n",
       "      <td>13853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 288 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp  13:00  14:00  15:00  16:00  17:00  18:00  19:00  20:00  21:00  \\\n",
       "0          10971  17074  16751  13127  14313  12591   7747   3628   5997   \n",
       "0          12092  30845  23816  29557  23204  15980   9892   8865   2279   \n",
       "0           5766  23582  26507  62600  36530  40782  19567  10192  19797   \n",
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       "0              0   5362  27889  26901  21305  23969  17600  27401  28230   \n",
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       "0          17396  18346  13312  46736  37032  24093   4221  13189  36219   \n",
       "0          25829  38170  21443  13205   8028  20502  15481   5577  31001   \n",
       "0          15269  30983  29740  26452  30292  17397   7210   7103  12329   \n",
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       "0          19917  28442  19867  12910   7818  10029   9269   7009   7239   \n",
       "0           1784  26144  48610  32403  42044  34624  25015  30188  18576   \n",
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       "0          16737  27766  42622  16658    388    562  24221  24274  12866   \n",
       "\n",
       "timestamp  22:00  ...  03:00  04:00  05:00  06:00  07:00  08:00  09:00  10:00  \\\n",
       "0           2492  ...    295    253    415   1053    708   1519  13420  11455   \n",
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       "0           7854  ...    180    340    180    180    200    300    300    260   \n",
       "0          18265  ...    509   1733    939    831  10754   1784  12533  23551   \n",
       "0          15626  ...   1586   1075   1087    988   4860   4927  21820  20262   \n",
       "0          23656  ...   2499   4442   4924    339    292    171     53    114   \n",
       "0          31941  ...    847    253    245   1712   1408    263    758    439   \n",
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       "0              0  ...  11894   4634   4025  21111   7600   8068  13445   9408   \n",
       "0           6386  ...   3983   2479    102    640    530    266    581   1063   \n",
       "0           2213  ...    401    392    394    262    183   1578   9124   8210   \n",
       "0           4457  ...    781    264    719    366    576    194    449    569   \n",
       "0           8674  ...   2843   4336   2965   2072     46   1086    455    382   \n",
       "0           2955  ...    503    315    343    422   7204   8194  11864  15835   \n",
       "0          16772  ...    302    309    670    838   6237  12960  19177  41507   \n",
       "0           1838  ...    423    518    131    350    131    520    436    494   \n",
       "0          16013  ...    139   5843     97    386   1011    538   1235  30115   \n",
       "0          12158  ...   1105   2687    958   2510    339   1548   1965    609   \n",
       "\n",
       "timestamp  11:00  12:00  \n",
       "0          13541  21750  \n",
       "0          54507  22821  \n",
       "0           1757   6388  \n",
       "0            546   8313  \n",
       "0           9288  20272  \n",
       "0          16314  25545  \n",
       "0            616  10203  \n",
       "0            180    180  \n",
       "0          21186  26484  \n",
       "0          42449  35300  \n",
       "0            219    138  \n",
       "0           4158   7671  \n",
       "0          35413  38573  \n",
       "0           2439   5621  \n",
       "0            308  11694  \n",
       "0          62775  18306  \n",
       "0           1188    478  \n",
       "0           4400  12245  \n",
       "0          25036  15167  \n",
       "0          25706  35735  \n",
       "0          20677  14188  \n",
       "0          22752  13241  \n",
       "0          12466  13853  \n",
       "\n",
       "[23 rows x 288 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df = condition_df.drop([\"Id\"], axis =1 )\n",
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <td>1.064316e+08</td>\n",
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       "      <td>1.065900e+08</td>\n",
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       "      <td>13963.0</td>\n",
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       "      <td>1.520241e+08</td>\n",
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       "      <td>44674.0</td>\n",
       "      <td>4758.819444</td>\n",
       "      <td>2950.5</td>\n",
       "      <td>5813.521416</td>\n",
       "      <td>3.379703e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12212</td>\n",
       "      <td>13468</td>\n",
       "      <td>14119</td>\n",
       "      <td>20368</td>\n",
       "      <td>14558</td>\n",
       "      <td>3216</td>\n",
       "      <td>201</td>\n",
       "      <td>2602</td>\n",
       "      <td>5469</td>\n",
       "      <td>6386</td>\n",
       "      <td>...</td>\n",
       "      <td>581</td>\n",
       "      <td>1063</td>\n",
       "      <td>308</td>\n",
       "      <td>11694</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65955.0</td>\n",
       "      <td>6394.791667</td>\n",
       "      <td>3295.0</td>\n",
       "      <td>8168.104049</td>\n",
       "      <td>6.671792e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7903</td>\n",
       "      <td>33460</td>\n",
       "      <td>27786</td>\n",
       "      <td>22705</td>\n",
       "      <td>14429</td>\n",
       "      <td>4687</td>\n",
       "      <td>22330</td>\n",
       "      <td>10001</td>\n",
       "      <td>5265</td>\n",
       "      <td>2213</td>\n",
       "      <td>...</td>\n",
       "      <td>9124</td>\n",
       "      <td>8210</td>\n",
       "      <td>62775</td>\n",
       "      <td>18306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90108.0</td>\n",
       "      <td>14561.930556</td>\n",
       "      <td>9879.0</td>\n",
       "      <td>15928.841954</td>\n",
       "      <td>2.537280e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3981</td>\n",
       "      <td>9476</td>\n",
       "      <td>9403</td>\n",
       "      <td>8488</td>\n",
       "      <td>1713</td>\n",
       "      <td>9661</td>\n",
       "      <td>9030</td>\n",
       "      <td>5152</td>\n",
       "      <td>4920</td>\n",
       "      <td>4457</td>\n",
       "      <td>...</td>\n",
       "      <td>449</td>\n",
       "      <td>569</td>\n",
       "      <td>1188</td>\n",
       "      <td>478</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>5028.975694</td>\n",
       "      <td>4353.5</td>\n",
       "      <td>4314.739364</td>\n",
       "      <td>1.861698e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5184</td>\n",
       "      <td>9186</td>\n",
       "      <td>7809</td>\n",
       "      <td>6898</td>\n",
       "      <td>821</td>\n",
       "      <td>2379</td>\n",
       "      <td>5261</td>\n",
       "      <td>6716</td>\n",
       "      <td>4946</td>\n",
       "      <td>8674</td>\n",
       "      <td>...</td>\n",
       "      <td>455</td>\n",
       "      <td>382</td>\n",
       "      <td>4400</td>\n",
       "      <td>12245</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16569.0</td>\n",
       "      <td>4358.763889</td>\n",
       "      <td>4119.5</td>\n",
       "      <td>3266.541230</td>\n",
       "      <td>1.067029e+07</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19917</td>\n",
       "      <td>28442</td>\n",
       "      <td>19867</td>\n",
       "      <td>12910</td>\n",
       "      <td>7818</td>\n",
       "      <td>10029</td>\n",
       "      <td>9269</td>\n",
       "      <td>7009</td>\n",
       "      <td>7239</td>\n",
       "      <td>2955</td>\n",
       "      <td>...</td>\n",
       "      <td>11864</td>\n",
       "      <td>15835</td>\n",
       "      <td>25036</td>\n",
       "      <td>15167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52132.0</td>\n",
       "      <td>9842.781250</td>\n",
       "      <td>7339.0</td>\n",
       "      <td>10336.730772</td>\n",
       "      <td>1.068480e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1784</td>\n",
       "      <td>26144</td>\n",
       "      <td>48610</td>\n",
       "      <td>32403</td>\n",
       "      <td>42044</td>\n",
       "      <td>34624</td>\n",
       "      <td>25015</td>\n",
       "      <td>30188</td>\n",
       "      <td>18576</td>\n",
       "      <td>16772</td>\n",
       "      <td>...</td>\n",
       "      <td>19177</td>\n",
       "      <td>41507</td>\n",
       "      <td>25706</td>\n",
       "      <td>35735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109032.0</td>\n",
       "      <td>21556.128472</td>\n",
       "      <td>21775.0</td>\n",
       "      <td>19038.389450</td>\n",
       "      <td>3.624603e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2324</td>\n",
       "      <td>26545</td>\n",
       "      <td>458</td>\n",
       "      <td>296</td>\n",
       "      <td>396</td>\n",
       "      <td>721</td>\n",
       "      <td>10927</td>\n",
       "      <td>390</td>\n",
       "      <td>1838</td>\n",
       "      <td>...</td>\n",
       "      <td>436</td>\n",
       "      <td>494</td>\n",
       "      <td>20677</td>\n",
       "      <td>14188</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37775.0</td>\n",
       "      <td>4495.090278</td>\n",
       "      <td>1314.5</td>\n",
       "      <td>5921.838513</td>\n",
       "      <td>3.506817e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4475</td>\n",
       "      <td>9879</td>\n",
       "      <td>19711</td>\n",
       "      <td>21423</td>\n",
       "      <td>13701</td>\n",
       "      <td>20150</td>\n",
       "      <td>19552</td>\n",
       "      <td>18239</td>\n",
       "      <td>14322</td>\n",
       "      <td>16013</td>\n",
       "      <td>...</td>\n",
       "      <td>1235</td>\n",
       "      <td>30115</td>\n",
       "      <td>22752</td>\n",
       "      <td>13241</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36760.0</td>\n",
       "      <td>9824.736111</td>\n",
       "      <td>8241.0</td>\n",
       "      <td>8946.603825</td>\n",
       "      <td>8.004172e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16737</td>\n",
       "      <td>27766</td>\n",
       "      <td>42622</td>\n",
       "      <td>16658</td>\n",
       "      <td>388</td>\n",
       "      <td>562</td>\n",
       "      <td>24221</td>\n",
       "      <td>24274</td>\n",
       "      <td>12866</td>\n",
       "      <td>12158</td>\n",
       "      <td>...</td>\n",
       "      <td>1965</td>\n",
       "      <td>609</td>\n",
       "      <td>12466</td>\n",
       "      <td>13853</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68211.0</td>\n",
       "      <td>14953.840278</td>\n",
       "      <td>11408.0</td>\n",
       "      <td>15162.249076</td>\n",
       "      <td>2.298938e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23 rows × 294 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp  13:00  14:00  15:00  16:00  17:00  18:00  19:00  20:00  21:00  \\\n",
       "0          10971  17074  16751  13127  14313  12591   7747   3628   5997   \n",
       "0          12092  30845  23816  29557  23204  15980   9892   8865   2279   \n",
       "0           5766  23582  26507  62600  36530  40782  19567  10192  19797   \n",
       "0           6024  12516  19457  11004  15760   9629   9633  10585  14169   \n",
       "0          15950  17506  17953   7259   9337    838   6650   6212   5160   \n",
       "0              0   5362  27889  26901  21305  23969  17600  27401  28230   \n",
       "0           8846  24753  20679    924    229  13181  16471  14487  12526   \n",
       "0          17396  18346  13312  46736  37032  24093   4221  13189  36219   \n",
       "0          25829  38170  21443  13205   8028  20502  15481   5577  31001   \n",
       "0          15269  30983  29740  26452  30292  17397   7210   7103  12329   \n",
       "0          29278  11190   9113  12873    635   1208    753   4645   1269   \n",
       "0          36873  29568  18006  35299  10799   2109  24114  15290  13781   \n",
       "0          13101  20585  13030  18174  25075  29275  28359  20768  23365   \n",
       "0          24065   4405  13715   6910     85  12299   6713   1607   3959   \n",
       "0          12212  13468  14119  20368  14558   3216    201   2602   5469   \n",
       "0           7903  33460  27786  22705  14429   4687  22330  10001   5265   \n",
       "0           3981   9476   9403   8488   1713   9661   9030   5152   4920   \n",
       "0           5184   9186   7809   6898    821   2379   5261   6716   4946   \n",
       "0          19917  28442  19867  12910   7818  10029   9269   7009   7239   \n",
       "0           1784  26144  48610  32403  42044  34624  25015  30188  18576   \n",
       "0              0   2324  26545    458    296    396    721  10927    390   \n",
       "0           4475   9879  19711  21423  13701  20150  19552  18239  14322   \n",
       "0          16737  27766  42622  16658    388    562  24221  24274  12866   \n",
       "\n",
       "timestamp  22:00  ...  09:00  10:00  11:00  12:00  Id       Max          mean  \\\n",
       "0           2492  ...  13420  11455  13541  21750 NaN   68238.0   9291.072917   \n",
       "0          24152  ...  31988  34359  54507  22821 NaN  125759.0  12349.989583   \n",
       "0          33566  ...   1104   1029   1757   6388 NaN   84062.0  15910.142361   \n",
       "0          17316  ...     57     91    546   8313 NaN   79625.0  16625.145833   \n",
       "0           2548  ...   9961   6422   9288  20272 NaN   62302.0  10183.833333   \n",
       "0          49243  ...   4888   7034  16314  25545 NaN   56630.0  12016.170139   \n",
       "0          12723  ...    545   1306    616  10203 NaN   94588.0  19158.645833   \n",
       "0           7854  ...    300    260    180    180 NaN  130377.0  11771.927083   \n",
       "0          18265  ...  12533  23551  21186  26484 NaN   52696.0  10781.597222   \n",
       "0          15626  ...  21820  20262  42449  35300 NaN   71072.0  18691.312500   \n",
       "0          23656  ...     53    114    219    138 NaN   47793.0   8815.381944   \n",
       "0          31941  ...    758    439   4158   7671 NaN   63559.0  10510.902778   \n",
       "0          18589  ...  18408  54268  35413  38573 NaN   54389.0  15111.402778   \n",
       "0              0  ...  13445   9408   2439   5621 NaN   44674.0   4758.819444   \n",
       "0           6386  ...    581   1063    308  11694 NaN   65955.0   6394.791667   \n",
       "0           2213  ...   9124   8210  62775  18306 NaN   90108.0  14561.930556   \n",
       "0           4457  ...    449    569   1188    478 NaN   17000.0   5028.975694   \n",
       "0           8674  ...    455    382   4400  12245 NaN   16569.0   4358.763889   \n",
       "0           2955  ...  11864  15835  25036  15167 NaN   52132.0   9842.781250   \n",
       "0          16772  ...  19177  41507  25706  35735 NaN  109032.0  21556.128472   \n",
       "0           1838  ...    436    494  20677  14188 NaN   37775.0   4495.090278   \n",
       "0          16013  ...   1235  30115  22752  13241 NaN   36760.0   9824.736111   \n",
       "0          12158  ...   1965    609  12466  13853 NaN   68211.0  14953.840278   \n",
       "\n",
       "timestamp   median            SD           Var  \n",
       "0           6033.0  10544.907858  1.111951e+08  \n",
       "0           7392.0  15352.106665  2.356872e+08  \n",
       "0          11943.5  15883.908459  2.522985e+08  \n",
       "0          11487.0  17956.185594  3.224246e+08  \n",
       "0           7629.0  10854.605572  1.178225e+08  \n",
       "0           9158.0  11640.328959  1.354973e+08  \n",
       "0          11583.0  22532.377402  5.077080e+08  \n",
       "0           4860.0  16399.910460  2.689571e+08  \n",
       "0           8887.5  10020.852927  1.004175e+08  \n",
       "0          18072.5  16442.958575  2.703709e+08  \n",
       "0           4577.5  10316.569290  1.064316e+08  \n",
       "0           7207.5  10324.244167  1.065900e+08  \n",
       "0          13963.0  12329.806207  1.520241e+08  \n",
       "0           2950.5   5813.521416  3.379703e+07  \n",
       "0           3295.0   8168.104049  6.671792e+07  \n",
       "0           9879.0  15928.841954  2.537280e+08  \n",
       "0           4353.5   4314.739364  1.861698e+07  \n",
       "0           4119.5   3266.541230  1.067029e+07  \n",
       "0           7339.0  10336.730772  1.068480e+08  \n",
       "0          21775.0  19038.389450  3.624603e+08  \n",
       "0           1314.5   5921.838513  3.506817e+07  \n",
       "0           8241.0   8946.603825  8.004172e+07  \n",
       "0          11408.0  15162.249076  2.298938e+08  \n",
       "\n",
       "[23 rows x 294 columns]"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "condition_df['Max'] = my_df.max(axis = 1)\n",
    "condition_df['mean'] = my_df.mean(axis=1)\n",
    "condition_df['median'] = my_df.median(axis = 1)\n",
    "condition_df['SD'] = my_df.std(axis =1)\n",
    "condition_df['Var'] = my_df.var(axis =1)\n",
    "condition_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>54389.0</td>\n",
       "      <td>15111.402778</td>\n",
       "      <td>13963.0</td>\n",
       "      <td>12329.806207</td>\n",
       "      <td>1.520241e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>44674.0</td>\n",
       "      <td>4758.819444</td>\n",
       "      <td>2950.5</td>\n",
       "      <td>5813.521416</td>\n",
       "      <td>3.379703e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>65955.0</td>\n",
       "      <td>6394.791667</td>\n",
       "      <td>3295.0</td>\n",
       "      <td>8168.104049</td>\n",
       "      <td>6.671792e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>90108.0</td>\n",
       "      <td>14561.930556</td>\n",
       "      <td>9879.0</td>\n",
       "      <td>15928.841954</td>\n",
       "      <td>2.537280e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>5028.975694</td>\n",
       "      <td>4353.5</td>\n",
       "      <td>4314.739364</td>\n",
       "      <td>1.861698e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>16569.0</td>\n",
       "      <td>4358.763889</td>\n",
       "      <td>4119.5</td>\n",
       "      <td>3266.541230</td>\n",
       "      <td>1.067029e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>52132.0</td>\n",
       "      <td>9842.781250</td>\n",
       "      <td>7339.0</td>\n",
       "      <td>10336.730772</td>\n",
       "      <td>1.068480e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>109032.0</td>\n",
       "      <td>21556.128472</td>\n",
       "      <td>21775.0</td>\n",
       "      <td>19038.389450</td>\n",
       "      <td>3.624603e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>37775.0</td>\n",
       "      <td>4495.090278</td>\n",
       "      <td>1314.5</td>\n",
       "      <td>5921.838513</td>\n",
       "      <td>3.506817e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>36760.0</td>\n",
       "      <td>9824.736111</td>\n",
       "      <td>8241.0</td>\n",
       "      <td>8946.603825</td>\n",
       "      <td>8.004172e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>condition</td>\n",
       "      <td>68211.0</td>\n",
       "      <td>14953.840278</td>\n",
       "      <td>11408.0</td>\n",
       "      <td>15162.249076</td>\n",
       "      <td>2.298938e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "timestamp         Id       Max          mean   median            SD  \\\n",
       "0          condition   68238.0   9291.072917   6033.0  10544.907858   \n",
       "0          condition  125759.0  12349.989583   7392.0  15352.106665   \n",
       "0          condition   84062.0  15910.142361  11943.5  15883.908459   \n",
       "0          condition   79625.0  16625.145833  11487.0  17956.185594   \n",
       "0          condition   62302.0  10183.833333   7629.0  10854.605572   \n",
       "0          condition   56630.0  12016.170139   9158.0  11640.328959   \n",
       "0          condition   94588.0  19158.645833  11583.0  22532.377402   \n",
       "0          condition  130377.0  11771.927083   4860.0  16399.910460   \n",
       "0          condition   52696.0  10781.597222   8887.5  10020.852927   \n",
       "0          condition   71072.0  18691.312500  18072.5  16442.958575   \n",
       "0          condition   47793.0   8815.381944   4577.5  10316.569290   \n",
       "0          condition   63559.0  10510.902778   7207.5  10324.244167   \n",
       "0          condition   54389.0  15111.402778  13963.0  12329.806207   \n",
       "0          condition   44674.0   4758.819444   2950.5   5813.521416   \n",
       "0          condition   65955.0   6394.791667   3295.0   8168.104049   \n",
       "0          condition   90108.0  14561.930556   9879.0  15928.841954   \n",
       "0          condition   17000.0   5028.975694   4353.5   4314.739364   \n",
       "0          condition   16569.0   4358.763889   4119.5   3266.541230   \n",
       "0          condition   52132.0   9842.781250   7339.0  10336.730772   \n",
       "0          condition  109032.0  21556.128472  21775.0  19038.389450   \n",
       "0          condition   37775.0   4495.090278   1314.5   5921.838513   \n",
       "0          condition   36760.0   9824.736111   8241.0   8946.603825   \n",
       "0          condition   68211.0  14953.840278  11408.0  15162.249076   \n",
       "\n",
       "timestamp           Var  \n",
       "0          1.111951e+08  \n",
       "0          2.356872e+08  \n",
       "0          2.522985e+08  \n",
       "0          3.224246e+08  \n",
       "0          1.178225e+08  \n",
       "0          1.354973e+08  \n",
       "0          5.077080e+08  \n",
       "0          2.689571e+08  \n",
       "0          1.004175e+08  \n",
       "0          2.703709e+08  \n",
       "0          1.064316e+08  \n",
       "0          1.065900e+08  \n",
       "0          1.520241e+08  \n",
       "0          3.379703e+07  \n",
       "0          6.671792e+07  \n",
       "0          2.537280e+08  \n",
       "0          1.861698e+07  \n",
       "0          1.067029e+07  \n",
       "0          1.068480e+08  \n",
       "0          3.624603e+08  \n",
       "0          3.506817e+07  \n",
       "0          8.004172e+07  \n",
       "0          2.298938e+08  "
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "condition_df = condition_df[['Id', 'Max', 'mean', 'median', 'SD', 'Var']]\n",
    "condition_df['Id'].fillna('condition', inplace= True)\n",
    "condition_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "#condition_df.to_csv(\"two_week_condition.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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