SBT_06 Pandas.ipynb

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   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Pandas"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0422\u0440\u0430\u0434\u0438\u0446\u0438\u043e\u043d\u043d\u043e pandas \u0438\u043c\u043f\u043e\u0440\u0442\u0438\u0440\u0443\u044e\u0442 \u043f\u043e\u0434 \u0438\u043c\u0435\u043d\u0435\u043c pd:"
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    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0421\u043e\u0437\u0434\u0430\u0434\u0438\u043c \u043d\u0435\u0431\u043e\u043b\u044c\u0448\u0443\u044e \"\u0438\u0433\u0440\u0443\u0448\u0435\u0447\u043d\u0443\u044e\" \u0442\u0430\u0431\u043b\u0438\u0446\u0443, \u0447\u0442\u043e\u0431\u044b \u0440\u0430\u0437\u043e\u0431\u0440\u0430\u0442\u044c\u0441\u044f \u0441 \u043e\u0441\u043d\u043e\u0432\u0430\u043c\u0438:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'AAA' : [4,5,6,7], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "   AAA  BBB  CCC\n",
        "0    4   10  100\n",
        "1    5   20   50\n",
        "2    6   30  -30\n",
        "3    7   40  -50"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "\u0411\u0430\u0437\u043e\u0432\u044b\u0435 \u0438\u0434\u0438\u043e\u043c\u044b"
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     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix[df.AAA >= 5,'BBB'] = -1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> -1</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> -1</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> -1</td>\n",
        "      <td> -50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "   AAA  BBB  CCC\n",
        "0    4   10  100\n",
        "1    5   -1   50\n",
        "2    6   -1  -30\n",
        "3    7   -1  -50"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix[df.AAA >= 4,['BBB','CCC']] = [[0, 7], [555, 666], [111, 222], [453, 345]]\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td>   0</td>\n",
        "      <td>   7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 555</td>\n",
        "      <td> 666</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 111</td>\n",
        "      <td> 222</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 453</td>\n",
        "      <td> 345</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "   AAA  BBB  CCC\n",
        "0    4    0    7\n",
        "1    5  555  666\n",
        "2    6  111  222\n",
        "3    7  453  345"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df_mask = pd.DataFrame({'AAA' : [True] * 4, 'BBB' : [False] * 4,'CCC' : [True,False] * 2})\n",
      "df.where(df_mask,-1000)\n",
      "#df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td>-1000</td>\n",
        "      <td>  100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td>-1000</td>\n",
        "      <td>-1000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td>-1000</td>\n",
        "      <td>  555</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td>-1000</td>\n",
        "      <td>-1000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "   AAA   BBB   CCC\n",
        "0    4 -1000   100\n",
        "1    5 -1000 -1000\n",
        "2    6 -1000   555\n",
        "3    7 -1000 -1000"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'AAA' : [4,5,6,7], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]})\n",
      "df['logic'] = np.where(df['AAA'] > 5, 'high', 'low')\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>logic</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "   AAA  BBB  CCC logic\n",
        "0    4   10  100   low\n",
        "1    5   20   50   low\n",
        "2    6   30  -30  high\n",
        "3    7   40  -50  high"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0410\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u043e \u043c\u043e\u0436\u043d\u043e \u0440\u0430\u0437\u0431\u0438\u0432\u0430\u0442\u044c \u0442\u0430\u0431\u043b\u0438\u0446\u0443 \u043f\u043e \u0431\u0443\u043b\u0435\u0432\u0441\u043a\u0438\u043c \u0432\u044b\u0440\u0430\u0436\u0435\u043d\u0438\u044f\u043c:"
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dflow = df[df.AAA <= 5]\n",
      "dfhigh = df[df.AAA > 5]\n",
      "dflow"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>logic</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "      <td> low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "      <td> low</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "   AAA  BBB  CCC logic\n",
        "0    4   10  100   low\n",
        "1    5   20   50   low"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dfhigh"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>logic</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td>-30</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td>-50</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "   AAA  BBB  CCC logic\n",
        "2    6   30  -30  high\n",
        "3    7   40  -50  high"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u041a\u0440\u0438\u0442\u0435\u0440\u0438\u0438 \u043c\u043e\u0433\u0443\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043a\u043e\u043b\u043e\u043d\u043e\u043a:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>logic</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "   AAA  BBB  CCC logic\n",
        "0    4   10  100   low\n",
        "1    5   20   50   low\n",
        "2    6   30  -30  high\n",
        "3    7   40  -50  high"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "newseries = df.loc[(df['BBB'] < 25) & (df['CCC'] >= -40), 'AAA']\n",
      "newseries"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "0    4\n",
        "1    5\n",
        "Name: AAA, dtype: int64"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print type(newseries)\n",
      "print type(df)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<class 'pandas.core.series.Series'>\n",
        "<class 'pandas.core.frame.DataFrame'>\n"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print newseries[1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "5\n"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print df[1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "KeyError",
       "evalue": "1",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-22-ed3cf25e0d9f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mprint\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   1676\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1677\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1678\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1679\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1680\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.pyc\u001b[0m in \u001b[0;36m_getitem_column\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   1683\u001b[0m         \u001b[1;31m# get column\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1684\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1685\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1686\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1687\u001b[0m         \u001b[1;31m# duplicate columns & possible reduce dimensionaility\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\generic.pyc\u001b[0m in \u001b[0;36m_get_item_cache\u001b[1;34m(self, item)\u001b[0m\n\u001b[0;32m   1050\u001b[0m         \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1051\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1052\u001b[1;33m             \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1053\u001b[0m             \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1054\u001b[0m             \u001b[0mcache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mres\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\internals.pyc\u001b[0m in \u001b[0;36mget\u001b[1;34m(self, item, fastpath)\u001b[0m\n\u001b[0;32m   2563\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2564\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misnull\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2565\u001b[1;33m                 \u001b[0mloc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2566\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2567\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0misnull\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\index.pyc\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   1179\u001b[0m         \u001b[0mloc\u001b[0m \u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0munique\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpossibly\u001b[0m \u001b[0mslice\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mmask\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1180\u001b[0m         \"\"\"\n\u001b[1;32m-> 1181\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_values_from_object\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1182\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1183\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseries\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\index.pyd\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas\\index.c:3656)\u001b[1;34m()\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\index.pyd\u001b[0m in \u001b[0;36mpandas.index.IndexEngine.get_loc (pandas\\index.c:3534)\u001b[1;34m()\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\hashtable.pyd\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas\\hashtable.c:11911)\u001b[1;34m()\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\hashtable.pyd\u001b[0m in \u001b[0;36mpandas.hashtable.PyObjectHashTable.get_item (pandas\\hashtable.c:11864)\u001b[1;34m()\u001b[0m\n",
        "\u001b[1;31mKeyError\u001b[0m: 1"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print df['AAA']\n",
      "print type(df['AAA'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0    4\n",
        "1    5\n",
        "2    6\n",
        "3    7\n",
        "Name: AAA, dtype: int64\n",
        "<class 'pandas.core.series.Series'>\n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print type(df['AAA'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<class 'pandas.core.series.Series'>\n"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>logic</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "   AAA  BBB  CCC logic\n",
        "0    4   10  100   low\n",
        "1    5   20   50   low\n",
        "2    6   30  -30  high\n",
        "3    7   40  -50  high"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.loc[(df['BBB'] > 25) | (df['CCC'] >= 75), 'AAA'] = 0.1\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>logic</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 0.1</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5.0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "      <td>  low</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 0.1</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 0.1</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "      <td> high</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "   AAA  BBB  CCC logic\n",
        "0  0.1   10  100   low\n",
        "1  5.0   20   50   low\n",
        "2  0.1   30  -30  high\n",
        "3  0.1   40  -50  high"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u0439 \u044f\u0447\u0435\u0439\u043a\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u043c\u043e\u0436\u043d\u043e \u0443\u043f\u043e\u0440\u044f\u0434\u043e\u0447\u0438\u0442\u044c \u0441\u0442\u0440\u043e\u043a\u0438 \u043f\u043e \u0431\u043b\u0438\u0437\u043e\u0441\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0432 \u043e\u0434\u043d\u043e\u0439 \u0438\u0437 \u043a\u043e\u043b\u043e\u043d\u043e\u043a \u043a \u0437\u0430\u0434\u0430\u043d\u043d\u043e\u043c\u0443 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0438 argsort()"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'AAA' : [4,5,6,7], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]})\n",
      "value = 43.0\n",
      "#print type(df.CCC)\n",
      "#print type(df.CCC.abs().argsort())\n",
      "#print (df.CCC - value).abs().argsort()\n",
      "df42 = df.ix[(df.CCC - value).abs().argsort()]\n",
      "df42"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 43,
       "text": [
        "   AAA  BBB  CCC\n",
        "1    5   20   50\n",
        "0    4   10  100\n",
        "2    6   30  -30\n",
        "3    7   40  -50"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0415\u0441\u043b\u0438 \u0443 \u0432\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043f\u0438\u0441\u043e\u043a \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u0435\u0432, \u043f\u043e \u043a\u043e\u0442\u043e\u0440\u044b\u043c \u043d\u0443\u0436\u043d\u043e \u043e\u0441\u0443\u0449\u0435\u0441\u0442\u0432\u0438\u0442\u044c \u0432\u044b\u0431\u043e\u0440\u043a\u0443:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "crit1 = df.AAA <= 5.5\n",
      "crit2 = df.BBB == 10.0\n",
      "crit3 = df.CCC > -40.0"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 45
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0412\u043c\u0435\u0441\u0442\u043e \u0442\u043e\u0433\u043e, \u0447\u0442\u043e\u0431\u044b \u043f\u0438\u0441\u0430\u0442\u044c \"\u0432 \u043b\u043e\u0431\":"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "all_crit = crit1 & crit2 & crit3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 34
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u041b\u0443\u0447\u0448\u0435 (\u043e\u0441\u043e\u0431\u0435\u043d\u043d\u043e, \u0435\u0441\u043b\u0438 \u0440\u0435\u0447\u044c \u0438\u0434\u0435\u0442 \u043f\u0440\u0430\u0432\u0434\u0430 \u043e \u0441\u043f\u0438\u0441\u043a\u0435, \u0430 \u043d\u0435 \u043e \u0442\u0440\u0451\u0445 \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u044f\u0445) \u0432\u043e\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0439 \u043f\u0438\u0442\u043e\u043d\u043e\u0432\u0441\u043a\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0435\u0439 reduce:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "crit_list = [crit1, crit2, crit3]\n",
      "all_crit = reduce(lambda x, y: x & y, crit_list)\n",
      "df[all_crit]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 47,
       "text": [
        "   AAA  BBB  CCC\n",
        "0    4   10  100"
       ]
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>\u0412\u043e\u043f\u0440\u043e\u0441:</b>\n",
      "\u0435\u0441\u043b\u0438 \u0432\u043c\u0435\u0441\u0442\u043e reduce \u043d\u0430\u043f\u0438\u0441\u0430\u0442\u044c functools.reduce, \u0432 \u0447\u0435\u043c \u0431\u0443\u0434\u0435\u0442 \u0440\u0430\u0437\u043b\u0438\u0447\u0438\u0435?"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "\u0412\u044b\u0431\u043e\u0440 \u044d\u043b\u0435\u043c\u0435\u043d\u0442\u043e\u0432"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'AAA' : [4,5,6,7], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]})\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "   AAA  BBB  CCC\n",
        "0    4   10  100\n",
        "1    5   20   50\n",
        "2    6   30  -30\n",
        "3    7   40  -50"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[(df.AAA <= 6) & (df.index.isin([0,2,4]))]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 38,
       "text": [
        "   AAA  BBB  CCC\n",
        "0    4   10  100\n",
        "2    6   30  -30"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = {'AAA' : [4,5,6,7], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]}\n",
      "\n",
      "df = pd.DataFrame(data=data,index=['foo','bar','boo','kar'])\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>foo</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>bar</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boo</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>kar</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 41,
       "text": [
        "     AAA  BBB  CCC\n",
        "foo    4   10  100\n",
        "bar    5   20   50\n",
        "boo    6   30  -30\n",
        "kar    7   40  -50"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0412 pandas \u0435\u0441\u0442\u044c \u0434\u0432\u0430 \u0442\u0438\u043f\u0430 \u0438\u043d\u0434\u0435\u043a\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f:\n",
      "1. Label-oriented\n",
      "1. Positional-oriented\n",
      "\n",
      "\u0415\u0441\u0442\u044c \u0438 \u043e\u0431\u043e\u0431\u0449\u0435\u043d\u043d\u044b\u0439 \u0432\u0430\u0440\u0438\u0430\u043d\u0442. \u041d\u0430\u0447\u043d\u0435\u043c \u0441 Label-oriented:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.loc['bar':'kar']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>bar</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td> 50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boo</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td>-30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>kar</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td>-50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 42,
       "text": [
        "     AAA  BBB  CCC\n",
        "bar    5   20   50\n",
        "boo    6   30  -30\n",
        "kar    7   40  -50"
       ]
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u043f\u0440\u0438 \u0442\u0430\u043a\u043e\u043c \u0438\u043d\u0434\u0435\u043a\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043e\u0431\u0430 \u043a\u043e\u043d\u0446\u0430 \u0438\u043d\u0442\u0435\u0440\u0432\u0430\u043b\u0430 \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0442\u0441\u044f \u0432 \u0438\u043d\u0442\u0435\u0440\u0432\u0430\u043b. \u0412\u0442\u043e\u0440\u043e\u0439 \u0432\u0430\u0440\u0438\u0430\u043d\u0442 - positional-oriented, \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u043d\u0435\u043c\u043d\u043e\u0433\u043e \u0438\u043d\u0430\u0447\u0435. \u0414\u043b\u044f \u043d\u0435\u0433\u043e \u0432\u043c\u0435\u0441\u0442\u043e \"loc\" \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442\u0441\u044f \"iloc\", \u0430 \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0439 \u0438\u043d\u0434\u0435\u043a\u0441 \u0437\u0434\u0435\u0441\u044c \u043d\u0435 \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442\u0441\u044f:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.iloc[1:3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>bar</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td> 50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boo</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td>-30</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 44,
       "text": [
        "     AAA  BBB  CCC\n",
        "bar    5   20   50\n",
        "boo    6   30  -30"
       ]
      }
     ],
     "prompt_number": 44
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0422\u0435\u0445 \u0436\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u043c\u043e\u0436\u043d\u043e \u0434\u043e\u0431\u0438\u0442\u044c\u0441\u044f \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \".ix\" :"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix[1:3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>bar</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td> 50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boo</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td>-30</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 46,
       "text": [
        "     AAA  BBB  CCC\n",
        "bar    5   20   50\n",
        "boo    6   30  -30"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix['bar':'kar']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>bar</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td> 50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boo</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td>-30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>kar</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td>-50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 47,
       "text": [
        "     AAA  BBB  CCC\n",
        "bar    5   20   50\n",
        "boo    6   30  -30\n",
        "kar    7   40  -50"
       ]
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u041d\u043e \u0447\u0442\u043e \u0436\u0435 \u0431\u0443\u0434\u0435\u0442, \u0435\u0441\u043b\u0438 \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u043c\u0435\u0442\u043e\u043a \u0441\u0442\u0440\u043e\u043a \u0431\u0443\u0434\u0443\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0446\u0435\u043b\u044b\u0435 \u0447\u0438\u0441\u043b\u0430? \u041e\u0447\u0435\u0432\u0438\u0434\u043d\u043e, \u0442\u043e\u0433\u0434\u0430 \u0432\u043e\u0437\u043d\u0438\u043a\u0430\u0435\u0442 \u043d\u0435\u043e\u0434\u043d\u043e\u0437\u043d\u0430\u0447\u043d\u043e\u0441\u0442\u044c \u043f\u0440\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0438 \".ix\":"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df2 = pd.DataFrame(data=data,index=[1,2,3,4])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 48
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0418\u043d\u0434\u0435\u043a\u0441 0 \u043d\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043b\u0441\u044f, \u0447\u0442\u043e\u0431\u044b \u043f\u043e\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u0434\u043d\u0443 \u0438\u043d\u0442\u0435\u0440\u0435\u0441\u043d\u0443\u044e \u043e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u044c \u0440\u0430\u0437\u0440\u0435\u0448\u0435\u043d\u0438\u044f \u044d\u0442\u043e\u0439 \u043d\u0435\u043e\u0434\u043d\u043e\u0437\u043d\u0430\u0447\u043d\u043e\u0441\u0442\u0438. \u0415\u0441\u043b\u0438 \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0441\u0440\u0435\u0437 \u0441 0:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df2.ix[0:3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 51,
       "text": [
        "   AAA  BBB  CCC\n",
        "1    4   10  100\n",
        "2    5   20   50\n",
        "3    6   30  -30"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0412\u0438\u0434\u0438\u043c, \u0447\u0442\u043e \u043f\u0440\u043e\u0438\u0437\u043e\u0448\u043b\u043e position-oriented \u0438\u043d\u0434\u0435\u043a\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435. \u0422\u0435\u043f\u0435\u0440\u044c \u043f\u043e\u043f\u0440\u043e\u0431\u0443\u0435\u043c \u0441 \u0435\u0434\u0438\u043d\u0438\u0446\u044b:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df2.ix[1:3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 52,
       "text": [
        "   AAA  BBB  CCC\n",
        "1    4   10  100\n",
        "2    5   20   50\n",
        "3    6   30  -30"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0417\u0434\u0435\u0441\u044c \u0443\u0436\u0435 label-based. \u0410 \"iloc\" \u0438 \"loc\" \u0440\u0430\u0431\u043e\u0442\u0430\u044e\u0442, \u0440\u0430\u0437\u0443\u043c\u0435\u0435\u0442\u0441\u044f, \u043f\u043e-\u043f\u0440\u0435\u0436\u043d\u0435\u043c\u0443. \u0418 \u0432 \u0441\u043b\u0443\u0447\u0430\u0435 \u0446\u0435\u043b\u043e\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u044b\u0445 \u0438\u043d\u0434\u0435\u043a\u0441\u043e\u0432 \u043e\u043f\u0440\u0430\u0432\u0434\u044b\u0432\u0430\u044e\u0442 \u0441\u0432\u043e\u0435 \u0441\u0443\u0449\u0435\u0441\u0442\u0432\u043e\u0432\u0430\u043d\u0438\u0435, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044f \u043d\u0435 \u0434\u0443\u043c\u0430\u0442\u044c \u043e \u0442\u043e\u043c, \u043a\u0430\u043a \u0431\u0443\u0434\u0435\u0442 \u0440\u0430\u0437\u0440\u0435\u0448\u0430\u0442\u044c\u0441\u044f \u043d\u0435\u043e\u0434\u043d\u043e\u0437\u043d\u0430\u0447\u043d\u043e\u0441\u0442\u044c. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0414\u043b\u044f \u0438\u043d\u0432\u0435\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043c\u0430\u0441\u043a\u0438 \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043e\u0431\u0435\u0440\u0430\u0442\u043e\u0440 \u043e\u0431\u0440\u0430\u0449\u0435\u043d\u0438\u044f ~:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[~((df.AAA <= 6) & (df.index.isin([0,2,4])))]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>foo</th>\n",
        "      <td> 4</td>\n",
        "      <td> 10</td>\n",
        "      <td> 100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>bar</th>\n",
        "      <td> 5</td>\n",
        "      <td> 20</td>\n",
        "      <td>  50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boo</th>\n",
        "      <td> 6</td>\n",
        "      <td> 30</td>\n",
        "      <td> -30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>kar</th>\n",
        "      <td> 7</td>\n",
        "      <td> 40</td>\n",
        "      <td> -50</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 54,
       "text": [
        "     AAA  BBB  CCC\n",
        "foo    4   10  100\n",
        "bar    5   20   50\n",
        "boo    6   30  -30\n",
        "kar    7   40  -50"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "\u041f\u0430\u043d\u0435\u043b\u0438"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "rng = pd.date_range('1/1/2013', periods=100, freq='D')\n",
      "data = np.random.randn(100, 4)\n",
      "cols = ['A', 'B', 'C', 'D']\n",
      "\n",
      "df1, df2, df3 = pd.DataFrame(data, rng, cols), pd.DataFrame(data, rng, cols),\\\n",
      "                pd.DataFrame(data, rng, cols)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pf = pd.Panel({'df1':df1,'df2':df2,'df3':df3})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pf"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 58,
       "text": [
        "<class 'pandas.core.panel.Panel'>\n",
        "Dimensions: 3 (items) x 100 (major_axis) x 4 (minor_axis)\n",
        "Items axis: df1 to df3\n",
        "Major_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00\n",
        "Minor_axis axis: A to D"
       ]
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pf = pf.transpose(2,0,1)\n",
      "pf"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 60,
       "text": [
        "<class 'pandas.core.panel.Panel'>\n",
        "Dimensions: 4 (items) x 3 (major_axis) x 100 (minor_axis)\n",
        "Items axis: A to D\n",
        "Major_axis axis: df1 to df3\n",
        "Minor_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00"
       ]
      }
     ],
     "prompt_number": 60
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pf['E'] = pd.DataFrame(data, rng, cols)\n",
      "pf"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 61,
       "text": [
        "<class 'pandas.core.panel.Panel'>\n",
        "Dimensions: 5 (items) x 3 (major_axis) x 100 (minor_axis)\n",
        "Items axis: A to E\n",
        "Major_axis axis: df1 to df3\n",
        "Minor_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00"
       ]
      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pf = pf.transpose(1,2,0)\n",
      "pf"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 62,
       "text": [
        "<class 'pandas.core.panel.Panel'>\n",
        "Dimensions: 3 (items) x 100 (major_axis) x 5 (minor_axis)\n",
        "Items axis: df1 to df3\n",
        "Major_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00\n",
        "Minor_axis axis: A to E"
       ]
      }
     ],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pf.loc[:,:,'F'] = pd.DataFrame(data, rng, cols)\n",
      "pf"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 63,
       "text": [
        "<class 'pandas.core.panel.Panel'>\n",
        "Dimensions: 3 (items) x 100 (major_axis) x 6 (minor_axis)\n",
        "Items axis: df1 to df3\n",
        "Major_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00\n",
        "Minor_axis axis: A to F"
       ]
      }
     ],
     "prompt_number": 63
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "\u0414\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0414\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0438 \u0437\u0430\u043c\u0435\u043d\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043d\u0438\u0445 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0438 applymap:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'AAA' : [1,2,1,3], 'BBB' : [1,1,2,2], 'CCC' : [2,1,3,1]})\n",
      "source_cols = df.columns\n",
      "new_cols = [str(x) + \"_cat\" for x in source_cols]\n",
      "categories = {1 : 'Alpha', 2 : 'Beta', 3 : 'Charlie'}\n",
      "df[new_cols] = df[source_cols].applymap(categories.get)\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "      <th>CCC</th>\n",
        "      <th>AAA_cat</th>\n",
        "      <th>BBB_cat</th>\n",
        "      <th>CCC_cat</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td>   Alpha</td>\n",
        "      <td> Alpha</td>\n",
        "      <td>    Beta</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td>    Beta</td>\n",
        "      <td> Alpha</td>\n",
        "      <td>   Alpha</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "      <td>   Alpha</td>\n",
        "      <td>  Beta</td>\n",
        "      <td> Charlie</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> Charlie</td>\n",
        "      <td>  Beta</td>\n",
        "      <td>   Alpha</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 64,
       "text": [
        "   AAA  BBB  CCC  AAA_cat BBB_cat  CCC_cat\n",
        "0    1    1    2    Alpha   Alpha     Beta\n",
        "1    2    1    1     Beta   Alpha    Alpha\n",
        "2    1    2    3    Alpha    Beta  Charlie\n",
        "3    3    2    1  Charlie    Beta    Alpha"
       ]
      }
     ],
     "prompt_number": 64
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "\u041c\u0435\u0442\u043e\u0434 groupby"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'AAA' : [1,1,1,2,2,2,3,3], 'BBB' : [2,1,3,4,5,1,2,3]})\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1</td>\n",
        "      <td> 3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 2</td>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 2</td>\n",
        "      <td> 5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 66,
       "text": [
        "   AAA  BBB\n",
        "0    1    2\n",
        "1    1    1\n",
        "2    1    3\n",
        "3    2    4\n",
        "4    2    5\n",
        "5    2    1\n",
        "6    3    2\n",
        "7    3    3"
       ]
      }
     ],
     "prompt_number": 66
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u041c\u0438\u043d\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0432 \u043a\u043e\u043b\u043e\u043d\u043a\u0435 \"BBB\" \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0438\u0437 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \"AAA\":"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.loc[df.groupby(\"AAA\")[\"BBB\"].idxmin()]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 72,
       "text": [
        "   AAA  BBB\n",
        "1    1    1\n",
        "5    2    1\n",
        "6    3    2"
       ]
      }
     ],
     "prompt_number": 72
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u0422\u043e \u0436\u0435 \u0441\u0430\u043c\u043e\u0435, \u043d\u043e \u0434\u0440\u0443\u0433\u0438\u043c \u0441\u043f\u043e\u0441\u043e\u0431\u043e\u043c:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.sort(\"BBB\").groupby(\"AAA\", as_index=False).first()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>AAA</th>\n",
        "      <th>BBB</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 78,
       "text": [
        "   AAA  BBB\n",
        "0    1    1\n",
        "1    2    1\n",
        "2    3    2"
       ]
      }
     ],
     "prompt_number": 78
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0437\u0434\u0435\u0441\u044c \u043c\u044b \u0443\u0436\u0435 \u043f\u043e\u0442\u0435\u0440\u044f\u043b\u0438 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e\u0431 \u0438\u043d\u0434\u0435\u043a\u0441\u0430\u0445 \u0441\u0442\u0440\u043e\u043a, \u0432 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0434\u043e\u0441\u0442\u0438\u0433\u0430\u043b\u0441\u044f \u043c\u0438\u043d\u0438\u043c\u0443\u043c."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Multindexing"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'row' : [0,1,2],\\\n",
      "                   'One_X' : [1.1,1.1,1.1],\\\n",
      "                   'One_Y' : [1.2,1.2,1.2],\\\n",
      "                   'Two_X' : [1.11,1.11,1.11],\\\n",
      "                   'Two_Y' : [1.22,1.22,1.22]})\n",
      "\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>One_X</th>\n",
        "      <th>One_Y</th>\n",
        "      <th>Two_X</th>\n",
        "      <th>Two_Y</th>\n",
        "      <th>row</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1.1</td>\n",
        "      <td> 1.2</td>\n",
        "      <td> 1.11</td>\n",
        "      <td> 1.22</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1.1</td>\n",
        "      <td> 1.2</td>\n",
        "      <td> 1.11</td>\n",
        "      <td> 1.22</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1.1</td>\n",
        "      <td> 1.2</td>\n",
        "      <td> 1.11</td>\n",
        "      <td> 1.22</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 79,
       "text": [
        "   One_X  One_Y  Two_X  Two_Y  row\n",
        "0    1.1    1.2   1.11   1.22    0\n",
        "1    1.1    1.2   1.11   1.22    1\n",
        "2    1.1    1.2   1.11   1.22    2"
       ]
      }
     ],
     "prompt_number": 79
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.set_index('row')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}