1주차_pandas기본.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3\n",
       "1    5\n",
       "2    6\n",
       "3    8\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = pd.Series([3,5,6,8])\n",
    "a"
   ]
  },
  {
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   "execution_count": 27,
   "metadata": {},
   "outputs": [
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       "   0  1    2   3\n",
       "0  3  5    6   8\n",
       "1  4  8    9  12\n",
       "2  1  5    8   6\n",
       "3 -3  8  123  55"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = pd.DataFrame([[3,5,6,8],[4,8,9,12],[1,5,8,6],[-3,8,123,55]])\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
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     "execution_count": 16,
     "metadata": {},
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   ],
   "source": [
    "c = pd.Series([1,2,3,4], index=['a','b','c','d'])\n",
    "c"
   ]
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   "execution_count": 13,
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      "text/plain": [
       "   0  1    2   3\n",
       "a  3  5    6   8\n",
       "b  4  8    9  12\n",
       "c  1  5    8   6\n",
       "d -3  8  123  55"
      ]
     },
     "execution_count": 13,
     "metadata": {},
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   ],
   "source": [
    "d = pd.DataFrame([[3,5,6,8],[4,8,9,12],[1,5,8,6],[-3,8,123,55]], index=['a','b','c','d'])\n",
    "d"
   ]
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   "execution_count": 79,
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      "text/plain": [
       "   A  B    C   D\n",
       "a  3  5    6   8\n",
       "b  4  8    9  12\n",
       "c  1  5    8   6\n",
       "d -3  8  123  55"
      ]
     },
     "execution_count": 79,
     "metadata": {},
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   ],
   "source": [
    "e = pd.DataFrame([[3,5,6,8],[4,8,9,12],[1,5,8,6],[-3,8,123,55]], index=['a','b','c','d'], columns=['A','B','C','D'])\n",
    "e"
   ]
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  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A     3\n",
       "B     5\n",
       "C     8\n",
       "D    15\n",
       "dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = pd.Series({'A':3,'B':5, 'C':8,'D':15})\n",
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   V1  V2\n",
       "A   1   5\n",
       "B   2  10\n",
       "C   3  15"
      ]
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     "execution_count": 35,
     "metadata": {},
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   "source": [
    "g = pd.DataFrame ( {'V1' : {'A':1,'B':2,'C':3}, 'V2':{'A':5,'B':10,'C':15} })\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>이름</th>\n",
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       "      <td>장태영</td>\n",
       "      <td>50</td>\n",
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       "      <td>게으름</td>\n",
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       "      <td>1</td>\n",
       "      <td>김동현</td>\n",
       "      <td>100</td>\n",
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      "text/plain": [
       "     이름   점수  성적   기타\n",
       "순번                   \n",
       "0   장태영   50  C+  게으름\n",
       "1   김동현  100  A+  성실함\n",
       "2   김규원   95  A+  잘생김"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = [['순번','이름','점수','성적','기타'], ['0','장태영','50','C+','게으름'],['1','김동현','100','A+','성실함'], ['2','김규원','95','A+','잘생김']]\n",
    "h = pd.DataFrame(csv[1:])\n",
    "h.columns = csv[0]\n",
    "h = h.set_index('순번')\n",
    "#h.index.names = [None]\n",
    "h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
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     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "c['a']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    3\n",
       "b    4\n",
       "c    1\n",
       "d   -3\n",
       "Name: A, dtype: int64"
      ]
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     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "e['A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    3\n",
       "B    5\n",
       "C    6\n",
       "D    8\n",
       "Name: a, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "e.loc['a']"
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       "   A  B    C   D\n",
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       "d -3  8  123  55"
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       "      <td>27</td>\n",
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       "      <td>d</td>\n",
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      "text/plain": [
       "   A  B    C   D   E\n",
       "a  3  5    6   8   9\n",
       "b  4  8    9  12   8\n",
       "c  1  5    8   6  27\n",
       "d -3  8  123  55  36"
      ]
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     "execution_count": 81,
     "metadata": {},
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   ],
   "source": [
    "e['E'] = [9,8,27,36]\n",
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
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       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>a</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>b</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>c</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>d</td>\n",
       "      <td>-3</td>\n",
       "      <td>8</td>\n",
       "      <td>123</td>\n",
       "      <td>55</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>e</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A  B    C   D   E\n",
       "a  3  5    6   8   9\n",
       "b  4  8    9  12   8\n",
       "c  1  5    8   6  27\n",
       "d -3  8  123  55  36\n",
       "e  7  8    9  10  11"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e.loc['e'] = [7,8,9,10,11]\n",
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    6\n",
       "3    8\n",
       "dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[a>5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "     A    B    C   D   E\n",
       "a  NaN  NaN    6   8   9\n",
       "b  NaN  8.0    9  12   8\n",
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       "d  NaN  8.0  123  55  36\n",
       "e  7.0  8.0    9  10  11"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e[e>5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "       A      B      C      D      E\n",
       "a   True   True  False  False  False\n",
       "b   True  False  False  False  False\n",
       "c   True   True  False  False  False\n",
       "d   True  False  False  False  False\n",
       "e  False  False  False  False  False"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e[e>5].isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "   a   b   c    d   e\n",
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       "C  6   9   8  123   9\n",
       "D  8  12   6   55  10\n",
       "E  9   8  27   36  11"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = pd.Series([1,2,3,4], index=['a','b','c','d'])\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "d    4\n",
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i2 = i.reindex(['d','a','b','c'])\n",
    "i2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F   NaN\n",
      "G   NaN\n",
      "H   NaN\n",
      "I   NaN\n",
      "dtype: float64\n",
      "--------------------\n",
      "Index(['a', 'b', 'c', 'd'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "i3 = i.reindex(['F','G','H','I']) #없는 인덱스에 이름 새로 지어주겠다고 하면 안됨\n",
    "print(i3)\n",
    "print('-'*20)\n",
    "print(i.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F    1\n",
       "G    2\n",
       "H    3\n",
       "I    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i.index = ['F','G','H','I']\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   A  B    C   D   E\n",
       "a  3  5    6   8   9\n",
       "b  4  8    9  12   8\n",
       "c  1  5    8   6  27\n",
       "d -3  8  123  55  36\n",
       "e  7  8    9  10  11"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = e\n",
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g['A'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "g['A'][2] = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <td>d</td>\n",
       "      <td>-3</td>\n",
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       "      <td>e</td>\n",
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       "      <td>8</td>\n",
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      "text/plain": [
       "   A  B    C   D   E\n",
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       "b  4  8    9  12   8\n",
       "c  5  5    8   6  27\n",
       "d -3  8  123  55  36\n",
       "e  7  8    9  10  11"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   A  B    C   D   E\n",
      "a  3  5    6   8   9\n",
      "b  4  8    9  12   8\n",
      "c  5  5    8   6  27\n",
      "d -3  8  123  55  36\n",
      "e  7  8    9  10  11\n",
      "--------------------\n",
      "   A  B    C   D   E\n",
      "a  3  5    6   8   9\n",
      "b  4  8    9  12   8\n",
      "c  1  5    8   6  27\n",
      "d -3  8  123  55  36\n",
      "e  7  8    9  10  11\n"
     ]
    }
   ],
   "source": [
    "k = e.copy()\n",
    "k\n",
    "k['A'][2] = 1\n",
    "print(e)\n",
    "print('-'*20)\n",
    "print(k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "   A  B    C   D   E\n",
       "a  3  5    6   8   9\n",
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       "d -3  8  123  55  36\n",
       "e  7  8    9  10  11"
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     "execution_count": 116,
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    "k.drop('c')"
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    {
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       "   A  B    C   E\n",
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    "k.drop('D', axis=1)"
   ]
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   "metadata": {},
   "outputs": [
    {
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    "l = k['b':'d']\n",
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   "metadata": {},
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    "m = k[:'a'] \n",
    "n = k['d':]"
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   "execution_count": 128,
   "metadata": {},
   "outputs": [
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    "o = m.append(n)\n",
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   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "add\n",
      "    0   1   2\n",
      "0   2   5   8\n",
      "1  11  14  13\n",
      "2  12  11  10\n",
      "--------------------\n",
      "susbstract\n",
      "   0  1  2\n",
      "0  0 -1 -2\n",
      "1 -3 -4 -1\n",
      "2  2  5  8\n",
      "--------------------\n",
      "div\n",
      "          0         1         2\n",
      "0  1.000000  0.666667  0.600000\n",
      "1  0.571429  0.555556  0.857143\n",
      "2  1.400000  2.666667  9.000000\n",
      "--------------------\n",
      "floordiv\n",
      "   0  1  2\n",
      "0  1  0  0\n",
      "1  0  0  0\n",
      "2  1  2  9\n",
      "multiply\n",
      "--------------------\n",
      "modular\n",
      "   0  1  2\n",
      "0  0  2  3\n",
      "1  4  5  6\n",
      "2  2  2  0\n",
      "--------------------\n",
      "power\n",
      "       0        1       2\n",
      "0      1        8     243\n",
      "1  16384  1953125  279936\n",
      "2  16807      512       9\n",
      "--------------------\n",
      "condition, return Boolean\n",
      "       0      1      2\n",
      "0  False  False  False\n",
      "1  False  False  False\n",
      "2   True   True   True\n",
      "--------------------\n"
     ]
    }
   ],
   "source": [
    "m1 = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]])\n",
    "m2 = pd.DataFrame([[1,3,5],[7,9,7],[5,3,1]])\n",
    "print('add')\n",
    "print(m1+m2)\n",
    "print('-'*20)\n",
    "print('susbstract')\n",
    "print(m1-m2)\n",
    "print('-'*20)\n",
    "print('div')\n",
    "print(m1/m2)\n",
    "print('-'*20)\n",
    "print('floordiv')\n",
    "print(m1//m2)\n",
    "print('multiply')\n",
    "print('-'*20)\n",
    "print('modular')\n",
    "print(m1%m2)\n",
    "print('-'*20)\n",
    "print('power')\n",
    "print(m1**m2)\n",
    "print('-'*20)\n",
    "print('condition, return Boolean')\n",
    "print(m1>m2)\n",
    "print('-'*20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "add\n",
      "    0   1   2\n",
      "0   4   8  12\n",
      "1   7  11  15\n",
      "2  10  14  18\n",
      "3  13  17  21\n",
      "--------------------\n",
      "susbstract\n",
      "   0  1  2\n",
      "0 -2 -4 -6\n",
      "1  1 -1 -3\n",
      "2  4  2  0\n",
      "3  7  5  3\n",
      "--------------------\n",
      "div\n",
      "          0         1         2\n",
      "0  0.333333  0.333333  0.333333\n",
      "1  1.333333  0.833333  0.666667\n",
      "2  2.333333  1.333333  1.000000\n",
      "3  3.333333  1.833333  1.333333\n",
      "--------------------\n",
      "floordiv\n",
      "   0  1  2\n",
      "0  0  0  0\n",
      "1  1  0  0\n",
      "2  2  1  1\n",
      "3  3  1  1\n",
      "multiply\n",
      "--------------------\n",
      "modular\n",
      "   0  1  2\n",
      "0  1  2  3\n",
      "1  1  5  6\n",
      "2  1  2  0\n",
      "3  1  5  3\n",
      "--------------------\n",
      "power\n",
      "      0        1           2\n",
      "0     1       64       19683\n",
      "1    64    15625    10077696\n",
      "2   343   262144   387420489\n",
      "3  1000  1771561  5159780352\n",
      "--------------------\n",
      "condition, return Boolean\n",
      "       0      1      2\n",
      "0  False  False  False\n",
      "1   True  False  False\n",
      "2   True   True  False\n",
      "3   True   True   True\n",
      "--------------------\n"
     ]
    }
   ],
   "source": [
    "m1 = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])\n",
    "s1 = pd.Series([3,6,9])\n",
    "print('add')\n",
    "print(m1+s1)\n",
    "print('-'*20)\n",
    "print('susbstract')\n",
    "print(m1-s1)\n",
    "print('-'*20)\n",
    "print('div')\n",
    "print(m1/s1)\n",
    "print('-'*20)\n",
    "print('floordiv')\n",
    "print(m1//s1)\n",
    "print('multiply')\n",
    "print('-'*20)\n",
    "print('modular')\n",
    "print(m1%s1)\n",
    "print('-'*20)\n",
    "print('power')\n",
    "print(m1**s1)\n",
    "print('-'*20)\n",
    "print('condition, return Boolean')\n",
    "print(m1>s1)\n",
    "print('-'*20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  2,  3],\n",
       "       [ 4,  5,  6],\n",
       "       [ 7,  8,  9],\n",
       "       [10, 11, 12]], dtype=int64)"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nd = m1.to_numpy()\n",
    "nd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12], dtype=int64)"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "nd.reshape(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  2,  3,  4],\n",
       "       [ 5,  6,  7,  8],\n",
       "       [ 9, 10, 11, 12]], dtype=int64)"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "nd.reshape(3,4)"
   ]
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   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
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    "m2"
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   "execution_count": 162,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     6\n",
       "1    15\n",
       "2    24\n",
       "3    33\n",
       "dtype: int64"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m1.sum(axis='columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "      <th></th>\n",
       "      <th>0</th>\n",
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       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>26</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "    0   1   2\n",
       "0   1   2   3\n",
       "1   5   7   9\n",
       "2  12  15  18\n",
       "3  22  26  30"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m1.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "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></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>6.500000</td>\n",
       "      <td>7.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>3.872983</td>\n",
       "      <td>3.872983</td>\n",
       "      <td>3.872983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>3.250000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>5.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>6.500000</td>\n",
       "      <td>7.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>8.750000</td>\n",
       "      <td>9.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               0          1          2\n",
       "count   4.000000   4.000000   4.000000\n",
       "mean    5.500000   6.500000   7.500000\n",
       "std     3.872983   3.872983   3.872983\n",
       "min     1.000000   2.000000   3.000000\n",
       "25%     3.250000   4.250000   5.250000\n",
       "50%     5.500000   6.500000   7.500000\n",
       "75%     7.750000   8.750000   9.750000\n",
       "max    10.000000  11.000000  12.000000"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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