ch09second.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from pandas import DataFrame, Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Joe</th>\n",
       "      <td>0.164279</td>\n",
       "      <td>-0.288185</td>\n",
       "      <td>0.860354</td>\n",
       "      <td>-2.456273</td>\n",
       "      <td>-1.154645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steve</th>\n",
       "      <td>-0.529059</td>\n",
       "      <td>-0.787231</td>\n",
       "      <td>-1.175355</td>\n",
       "      <td>0.405180</td>\n",
       "      <td>-1.227246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wes</th>\n",
       "      <td>-0.583101</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.451797</td>\n",
       "      <td>-0.445886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jim</th>\n",
       "      <td>-2.297013</td>\n",
       "      <td>0.741557</td>\n",
       "      <td>0.531242</td>\n",
       "      <td>-0.561197</td>\n",
       "      <td>-0.358583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travis</th>\n",
       "      <td>0.570748</td>\n",
       "      <td>0.366625</td>\n",
       "      <td>-0.298591</td>\n",
       "      <td>-0.699932</td>\n",
       "      <td>0.180338</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               a         b         c         d         e\n",
       "Joe     0.164279 -0.288185  0.860354 -2.456273 -1.154645\n",
       "Steve  -0.529059 -0.787231 -1.175355  0.405180 -1.227246\n",
       "Wes    -0.583101       NaN       NaN  0.451797 -0.445886\n",
       "Jim    -2.297013  0.741557  0.531242 -0.561197 -0.358583\n",
       "Travis  0.570748  0.366625 -0.298591 -0.699932  0.180338"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people = DataFrame(np.random.randn(5, 5),\n",
    "                   columns=['a', 'b', 'c', 'd', 'e'],\n",
    "                   index=['Joe', 'Steve', 'Wes', 'Jim', 'Travis'])\n",
    "people.ix[2:3, ['b', 'c']] = np.nan # 添加几个NA值\n",
    "people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>0.050642</td>\n",
       "      <td>0.039220</td>\n",
       "      <td>0.280882</td>\n",
       "      <td>-0.901469</td>\n",
       "      <td>-0.473398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>-1.413036</td>\n",
       "      <td>-0.022837</td>\n",
       "      <td>-0.322057</td>\n",
       "      <td>-0.078009</td>\n",
       "      <td>-0.792914</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            a         b         c         d         e\n",
       "one  0.050642  0.039220  0.280882 -0.901469 -0.473398\n",
       "two -1.413036 -0.022837 -0.322057 -0.078009 -0.792914"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "key = ['one', 'two', 'one', 'two', 'one']\n",
    "people.groupby(key).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Joe</th>\n",
       "      <td>0.050642</td>\n",
       "      <td>0.039220</td>\n",
       "      <td>0.280882</td>\n",
       "      <td>-0.901469</td>\n",
       "      <td>-0.473398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steve</th>\n",
       "      <td>-1.413036</td>\n",
       "      <td>-0.022837</td>\n",
       "      <td>-0.322057</td>\n",
       "      <td>-0.078009</td>\n",
       "      <td>-0.792914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wes</th>\n",
       "      <td>0.050642</td>\n",
       "      <td>0.039220</td>\n",
       "      <td>0.280882</td>\n",
       "      <td>-0.901469</td>\n",
       "      <td>-0.473398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jim</th>\n",
       "      <td>-1.413036</td>\n",
       "      <td>-0.022837</td>\n",
       "      <td>-0.322057</td>\n",
       "      <td>-0.078009</td>\n",
       "      <td>-0.792914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travis</th>\n",
       "      <td>0.050642</td>\n",
       "      <td>0.039220</td>\n",
       "      <td>0.280882</td>\n",
       "      <td>-0.901469</td>\n",
       "      <td>-0.473398</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               a         b         c         d         e\n",
       "Joe     0.050642  0.039220  0.280882 -0.901469 -0.473398\n",
       "Steve  -1.413036 -0.022837 -0.322057 -0.078009 -0.792914\n",
       "Wes     0.050642  0.039220  0.280882 -0.901469 -0.473398\n",
       "Jim    -1.413036 -0.022837 -0.322057 -0.078009 -0.792914\n",
       "Travis  0.050642  0.039220  0.280882 -0.901469 -0.473398"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people.groupby(key).transform(np.mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Joe</th>\n",
       "      <td>0.113637</td>\n",
       "      <td>-0.327405</td>\n",
       "      <td>0.579472</td>\n",
       "      <td>-1.554804</td>\n",
       "      <td>-0.681247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steve</th>\n",
       "      <td>0.883977</td>\n",
       "      <td>-0.764394</td>\n",
       "      <td>-0.853299</td>\n",
       "      <td>0.483189</td>\n",
       "      <td>-0.434331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wes</th>\n",
       "      <td>-0.633743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.353266</td>\n",
       "      <td>0.027512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jim</th>\n",
       "      <td>-0.883977</td>\n",
       "      <td>0.764394</td>\n",
       "      <td>0.853299</td>\n",
       "      <td>-0.483189</td>\n",
       "      <td>0.434331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travis</th>\n",
       "      <td>0.520106</td>\n",
       "      <td>0.327405</td>\n",
       "      <td>-0.579472</td>\n",
       "      <td>0.201538</td>\n",
       "      <td>0.653735</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               a         b         c         d         e\n",
       "Joe     0.113637 -0.327405  0.579472 -1.554804 -0.681247\n",
       "Steve   0.883977 -0.764394 -0.853299  0.483189 -0.434331\n",
       "Wes    -0.633743       NaN       NaN  1.353266  0.027512\n",
       "Jim    -0.883977  0.764394  0.853299 -0.483189  0.434331\n",
       "Travis  0.520106  0.327405 -0.579472  0.201538  0.653735"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def demean(arr):\n",
    "    return arr - arr.mean()\n",
    "\n",
    "demeaned = people.groupby(key).transform(demean)\n",
    "demeaned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>3.700743e-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.551115e-17</td>\n",
       "      <td>-7.401487e-17</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.551115e-17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                a    b             c             d             e\n",
       "one  3.700743e-17  0.0 -5.551115e-17 -7.401487e-17  0.000000e+00\n",
       "two  0.000000e+00  0.0  0.000000e+00  0.000000e+00  5.551115e-17"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demeaned.groupby(key).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>blue</th>\n",
       "      <th>red</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Joe</th>\n",
       "      <td>-1.072349</td>\n",
       "      <td>-3.244332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steve</th>\n",
       "      <td>0.715276</td>\n",
       "      <td>2.127817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wes</th>\n",
       "      <td>0.810232</td>\n",
       "      <td>0.514027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jim</th>\n",
       "      <td>-1.583890</td>\n",
       "      <td>3.318706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travis</th>\n",
       "      <td>1.451777</td>\n",
       "      <td>-0.789477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            blue       red\n",
       "Joe    -1.072349 -3.244332\n",
       "Steve   0.715276  2.127817\n",
       "Wes     0.810232  0.514027\n",
       "Jim    -1.583890  3.318706\n",
       "Travis  1.451777 -0.789477"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapping = {'a': 'red', 'b': 'red', 'c': 'blue',\n",
    "          'd': 'blue', 'e': 'red', 'f': 'orange'}\n",
    "\n",
    "by_column = people.groupby(mapping, axis=1)\n",
    "by_column.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a       red\n",
       "b       red\n",
       "c      blue\n",
       "d      blue\n",
       "e       red\n",
       "f    orange\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "map_series = Series(mapping)\n",
    "map_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>blue</th>\n",
       "      <th>red</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Joe</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steve</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wes</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jim</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travis</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        blue  red\n",
       "Joe        2    3\n",
       "Steve      2    3\n",
       "Wes        1    2\n",
       "Jim        2    3\n",
       "Travis     2    3"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people.groupby(map_series, axis=1).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.342105</td>\n",
       "      <td>-0.870905</td>\n",
       "      <td>0.360060</td>\n",
       "      <td>-2.206066</td>\n",
       "      <td>0.117201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.013084</td>\n",
       "      <td>1.266295</td>\n",
       "      <td>-0.053526</td>\n",
       "      <td>0.768802</td>\n",
       "      <td>0.848437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.252838</td>\n",
       "      <td>0.727597</td>\n",
       "      <td>0.092327</td>\n",
       "      <td>1.359451</td>\n",
       "      <td>-1.769912</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d         e\n",
       "3  1.342105 -0.870905  0.360060 -2.206066  0.117201\n",
       "5  0.013084  1.266295 -0.053526  0.768802  0.848437\n",
       "6  0.252838  0.727597  0.092327  1.359451 -1.769912"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people.groupby(len).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3</th>\n",
       "      <th>one</th>\n",
       "      <td>-0.025513</td>\n",
       "      <td>-2.077310</td>\n",
       "      <td>0.452118</td>\n",
       "      <td>-1.524466</td>\n",
       "      <td>-1.206672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>1.327967</td>\n",
       "      <td>1.206405</td>\n",
       "      <td>-0.092058</td>\n",
       "      <td>-1.491832</td>\n",
       "      <td>0.784333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>one</th>\n",
       "      <td>0.013084</td>\n",
       "      <td>1.266295</td>\n",
       "      <td>-0.053526</td>\n",
       "      <td>0.768802</td>\n",
       "      <td>0.848437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>two</th>\n",
       "      <td>0.252838</td>\n",
       "      <td>0.727597</td>\n",
       "      <td>0.092327</td>\n",
       "      <td>1.359451</td>\n",
       "      <td>-1.769912</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              a         b         c         d         e\n",
       "3 one -0.025513 -2.077310  0.452118 -1.524466 -1.206672\n",
       "  two  1.327967  1.206405 -0.092058 -1.491832  0.784333\n",
       "5 one  0.013084  1.266295 -0.053526  0.768802  0.848437\n",
       "6 two  0.252838  0.727597  0.092327  1.359451 -1.769912"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "key_list = ['one', 'one', 'one', 'two', 'two']\n",
    "people.groupby([len, key_list]).min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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