fetch_log_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetch log analysis\n",
    "\n",
    "Exploratory analysis of the stop times fetching log data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T16:17:00.013948Z",
     "start_time": "2020-03-19T16:17:00.004577Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "import os\n",
    "import modin.pandas as pd\n",
    "import requests\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the data to a pandas DataFrame and show the first rows. Also convert some  columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T15:30:30.880572Z",
     "start_time": "2020-03-19T15:28:33.539561Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[2m\u001b[36m(pid=200)\u001b[0m DtypeWarning: Columns (4) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "\u001b[2m\u001b[36m(pid=198)\u001b[0m DtypeWarning: Columns (4) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "\u001b[2m\u001b[36m(pid=199)\u001b[0m DtypeWarning: Columns (4) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "\u001b[2m\u001b[36m(pid=206)\u001b[0m DtypeWarning: Columns (4) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "\u001b[2m\u001b[36m(pid=209)\u001b[0m DtypeWarning: Columns (4) have mixed types.Specify dtype option on import or set low_memory=False.\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cod_stop</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>resp_status</th>\n",
       "      <th>resp_length</th>\n",
       "      <th>timeout</th>\n",
       "      <th>connection_error</th>\n",
       "      <th>max_connections</th>\n",
       "      <th>timeout_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actual_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-02-15 17:46:11.396055</th>\n",
       "      <td>8_06283</td>\n",
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       "      <td>200</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-15 17:46:11.394207</th>\n",
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       "      <td>0.795400</td>\n",
       "      <td>200</td>\n",
       "      <td>7515.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-15 17:46:11.394387</th>\n",
       "      <td>8_3444</td>\n",
       "      <td>0.834889</td>\n",
       "      <td>200</td>\n",
       "      <td>7407.0</td>\n",
       "      <td>False</td>\n",
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       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-15 17:46:11.395877</th>\n",
       "      <td>8_06884</td>\n",
       "      <td>1.041245</td>\n",
       "      <td>200</td>\n",
       "      <td>20115.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-15 17:46:11.393115</th>\n",
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       "      <td>200</td>\n",
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       "      <td>False</td>\n",
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       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>2020-03-17 10:45:42.742852</th>\n",
       "      <td>8_19420</td>\n",
       "      <td>10.532590</td>\n",
       "      <td>200</td>\n",
       "      <td>7419.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17 10:45:42.745405</th>\n",
       "      <td>8_08698</td>\n",
       "      <td>10.552473</td>\n",
       "      <td>200</td>\n",
       "      <td>11824.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>2020-03-17 10:45:42.745561</th>\n",
       "      <td>8_07505</td>\n",
       "      <td>10.598485</td>\n",
       "      <td>200</td>\n",
       "      <td>5070.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17 10:45:42.737376</th>\n",
       "      <td>8_23</td>\n",
       "      <td>10.661054</td>\n",
       "      <td>200</td>\n",
       "      <td>90164.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17 10:45:42.744747</th>\n",
       "      <td>8_17480</td>\n",
       "      <td>12.233006</td>\n",
       "      <td>200</td>\n",
       "      <td>53743.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12316697 rows x 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           cod_stop  resp_time resp_status  resp_length  \\\n",
       "actual_date                                                               \n",
       "2020-02-15 17:46:11.396055  8_06283   0.767585         200       3750.0   \n",
       "2020-02-15 17:46:11.394207  8_11647   0.795400         200       7515.0   \n",
       "2020-02-15 17:46:11.394387   8_3444   0.834889         200       7407.0   \n",
       "2020-02-15 17:46:11.395877  8_06884   1.041245         200      20115.0   \n",
       "2020-02-15 17:46:11.393115  8_50001   1.106854         200       2026.0   \n",
       "...                             ...        ...         ...          ...   \n",
       "2020-03-17 10:45:42.742852  8_19420  10.532590         200       7419.0   \n",
       "2020-03-17 10:45:42.745405  8_08698  10.552473         200      11824.0   \n",
       "2020-03-17 10:45:42.745561  8_07505  10.598485         200       5070.0   \n",
       "2020-03-17 10:45:42.737376     8_23  10.661054         200      90164.0   \n",
       "2020-03-17 10:45:42.744747  8_17480  12.233006         200      53743.0   \n",
       "\n",
       "                            timeout  connection_error  max_connections  \\\n",
       "actual_date                                                              \n",
       "2020-02-15 17:46:11.396055    False             False               25   \n",
       "2020-02-15 17:46:11.394207    False             False               25   \n",
       "2020-02-15 17:46:11.394387    False             False               25   \n",
       "2020-02-15 17:46:11.395877    False             False               25   \n",
       "2020-02-15 17:46:11.393115    False             False               25   \n",
       "...                             ...               ...              ...   \n",
       "2020-03-17 10:45:42.742852    False             False               25   \n",
       "2020-03-17 10:45:42.745405    False             False               25   \n",
       "2020-03-17 10:45:42.745561    False             False               25   \n",
       "2020-03-17 10:45:42.737376    False             False               25   \n",
       "2020-03-17 10:45:42.744747    False             False               25   \n",
       "\n",
       "                            timeout_time  \n",
       "actual_date                               \n",
       "2020-02-15 17:46:11.396055            60  \n",
       "2020-02-15 17:46:11.394207            60  \n",
       "2020-02-15 17:46:11.394387            60  \n",
       "2020-02-15 17:46:11.395877            60  \n",
       "2020-02-15 17:46:11.393115            60  \n",
       "...                                  ...  \n",
       "2020-03-17 10:45:42.742852            60  \n",
       "2020-03-17 10:45:42.745405            60  \n",
       "2020-03-17 10:45:42.745561            60  \n",
       "2020-03-17 10:45:42.737376            60  \n",
       "2020-03-17 10:45:42.744747            60  \n",
       "\n",
       "[12316697 rows x 8 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\n",
    "                 'fetch_log_parsed',\n",
    "                 parse_dates=['actual_date'],\n",
    "                 infer_datetime_format=True,\n",
    "                 index_col='actual_date',\n",
    "                 dtype={\n",
    "                        'resp_status': str,\n",
    "                        'resp_legth': float\n",
    "                        }\n",
    "                 )\n",
    "df['resp_length'] = pd.to_numeric(df['resp_length'], errors='coerce')\n",
    "#df = df['2020-02-12 00:00':]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T15:30:30.947339Z",
     "start_time": "2020-03-19T15:30:30.883040Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data from 2020-02-15T17:46:11.379125000 to 2020-03-17T10:45:42.745561000.\n"
     ]
    }
   ],
   "source": [
    "print('Data from ' + str(df.index.values.min()) + ' to ' + str(df.index.values.max()) +'.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Response time over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T16:10:06.080128Z",
     "start_time": "2020-03-19T16:09:47.413432Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/modin/error_message.py:46: UserWarning:\n",
      "\n",
      "User-defined function verification is still under development in Modin. The function provided is not verified.\n",
      "\n",
      "/opt/conda/lib/python3.7/site-packages/modin/error_message.py:32: UserWarning:\n",
      "\n",
      "`DataFrame.resample` defaulting to pandas implementation.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "minute_mean = df.query(\"resp_length > 0 & resp_status == '200' & timeout == False\").resample(\"30Min\").mean()\n",
    "# plt.figure()\n",
    "# plt.title('Response time over time of successful requests')\n",
    "# plt.xlabel('Date')\n",
    "# plt.ylabel('Response time (s)')\n",
    "# plt.plot(minute_mean['resp_time'])\n",
    "# #plt.hist([df.loc[df['resp_status'] == x, 'actual_date'] for x in error_codes], label=error_codes)\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T16:08:00.951077Z",
     "start_time": "2020-03-19T16:08:00.556924Z"
    }
   },
   "outputs": [
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "fig = px.line(\n",
    "              minute_mean,\n",
    "              x=minute_mean.index.to_pydatetime(),\n",
    "              y='resp_time')\n",
    "\n",
    "# Edit the layout\n",
    "fig.update_layout(title='Response time of successful requests over time',\n",
    "                  xaxis_title='Date',\n",
    "                  yaxis_title='Response time (s)')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Response status over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T17:12:04.948934Z",
     "start_time": "2020-03-19T17:12:02.189623Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/modin/error_message.py:32: UserWarning:\n",
      "\n",
      "`Series.unique` defaulting to pandas implementation.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "status_codes = df['resp_status'].unique()\n",
    "# plt.figure()\n",
    "# plt.title('Response status over time')\n",
    "# plt.xlabel('Date')\n",
    "# for status_code in status_codes:\n",
    "#     plt.plot(df.query(\"resp_status == '{status_code}'\".format(status_code=status_code)).resample(\"30Min\").count()['resp_status'], label=status_code)\n",
    "# plt.ylabel('Number of answers')\n",
    "# plt.legend()\n",
    "# # plt.twinx()\n",
    "# # plt.plot(df['cod_stop'].resample(\"30Min\").nunique(), color='purple')\n",
    "# # plt.ylabel('Number of stops')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T17:11:32.892535Z",
     "start_time": "2020-03-19T17:10:33.686968Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/modin/error_message.py:46: UserWarning:\n",
      "\n",
      "User-defined function verification is still under development in Modin. The function provided is not verified.\n",
      "\n",
      "/opt/conda/lib/python3.7/site-packages/modin/error_message.py:32: UserWarning:\n",
      "\n",
      "`DataFrame.resample` defaulting to pandas implementation.\n",
      "\n"
     ]
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\"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Response status over time\"}, \"xaxis\": {\"title\": {\"text\": \"Date\"}}, \"yaxis\": {\"title\": {\"text\": \"Number of answers\"}}},\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = go.Figure()\n",
    "for status_code in status_codes:\n",
    "    #plt.plot(df.query(\"resp_status == '{status_code}'\".format(status_code=status_code)).resample(\"30Min\").count()['resp_status'], label=status_code)\n",
    "    plot_df = (df\n",
    "                 .query(\"resp_status == '{status_code}'\"\n",
    "                 .format(status_code=status_code))\n",
    "                 .resample(\"30Min\")\n",
    "                 .count())\n",
    "    fig.add_trace(go.Scatter(\n",
    "                x=plot_df.index.to_pydatetime(),\n",
    "                y=plot_df['resp_status'],\n",
    "                name=status_code))\n",
    "    \n",
    "# Edit the layout\n",
    "fig.update_layout(title='Response status over time',\n",
    "                  xaxis_title='Date',\n",
    "                  yaxis_title='Number of answers')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Timeout ratio over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T17:17:27.315727Z",
     "start_time": "2020-03-19T17:17:25.002983Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/modin/error_message.py:32: UserWarning:\n",
      "\n",
      "`Series.resample` defaulting to pandas implementation.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "timeout_sampled = df['timeout'].resample(\"30Min\")\n",
    "timeout_ratio_sampled = timeout_sampled.sum()/timeout_sampled.count()\n",
    "# plt.figure()\n",
    "# plt.title('Timeout ratio over time')\n",
    "# plt.xlabel('Date')\n",
    "# plt.plot(timeout_ratio_sampled)\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-19T17:22:42.602189Z",
     "start_time": "2020-03-19T17:22:42.340911Z"
    }
   },
   "outputs": [
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    "fig = px.line(\n",
    "        x=timeout_ratio_sampled.index.to_pydatetime(),\n",
    "        y=timeout_ratio_sampled.values)\n",
    "\n",
    "# Edit the layout\n",
    "fig.update_layout(title='Timeout ratio over time',\n",
    "                  xaxis_title='Date',\n",
    "                  yaxis_title='Timeout ratio')\n",
    "\n",
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