{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# pandas层次化索引" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. 创建多层行索引" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1) 隐式构造\n", "\n", "最常见的方法是给DataFrame构造函数的index参数传递两个或更多的数组" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- Series也可以创建多层索引" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "张三 期中 40\n", " 期末 79\n", "李四 期中 88\n", " 期末 109\n", "Michael 期中 146\n", " 期末 51\n", "dtype: int64" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s = Series(data = np.random.randint(0,150,size = 6),\n", " index =[['张三','张三','李四','李四','Michael','Michael'],['期中','期末','期中','期末','期中','期末']] )\n", "s" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "from pandas import Series,DataFrame" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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PythonJavaPHP
张三期中8765129
期末14731120
李四期中383174
期末388699
Michael期中10712346
期末2114972
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" ], "text/plain": [ " Python Java PHP\n", "张三 期中 87 65 129\n", " 期末 147 31 120\n", "李四 期中 38 31 74\n", " 期末 38 86 99\n", "Michael 期中 107 123 46\n", " 期末 21 149 72" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = DataFrame(data = np.random.randint(0,150,size = (6,3)),\n", " columns = ['Python','Java','PHP'],\n", " index = [['张三','张三','李四','李四','Michael','Michael'],['期中','期末','期中','期末','期中','期末']])\n", "#隐式创建\n", "df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2) 显示构造pd.MultiIndex" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- 使用数组" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
张三期中3361104117
期末45209461
李四期中39941444
期末3867113111
Michael期中33539135
期末117875118
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "张三 期中 33 61 104 117\n", " 期末 45 20 94 61\n", "李四 期中 39 94 144 4\n", " 期末 38 67 113 111\n", "Michael 期中 33 5 39 135\n", " 期末 117 87 5 118" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2 = DataFrame(data = np.random.randint(0,150,size = (6,4)),\n", " columns = [\"Spring\",'Summer','Autumn','Winter'],\n", " index = pd.MultiIndex.from_arrays([['张三','张三','李四','李四','Michael','Michael'],['期中','期末','期中','期末','期中','期末']]))\n", "\n", "df2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- 使用tuple" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
张三期中315712434
期末134206055
李四期中337012847
期末955101117
Sara期中14114146147
期末1081147386
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "张三 期中 31 57 124 34\n", " 期末 134 20 60 55\n", "李四 期中 33 70 128 47\n", " 期末 9 55 101 117\n", "Sara 期中 14 114 146 147\n", " 期末 108 114 73 86" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3 = DataFrame(data = np.random.randint(0,150,size = (6,4)),\n", " columns = [\"Spring\",'Summer','Autumn','Winter'],\n", " index = pd.MultiIndex.from_tuples([('张三','期中'),('张三','期末'),('李四','期中'),('李四','期末'),('Sara','期中'),('Sara','期末')]))\n", "\n", "df3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- 使用product\n", "\n", " 最简单，推荐使用" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
张三middleA615864105
B118121881
endA135147141107
B97293156
SaramiddleA111909128
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LisamiddleA231426567
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "张三 middle A 61 58 64 105\n", " B 118 121 8 81\n", " end A 135 147 141 107\n", " B 97 29 31 56\n", "Sara middle A 111 90 9 128\n", " B 40 95 149 44\n", " end A 9 8 97 0\n", " B 70 16 60 10\n", "Lisa middle A 23 142 65 67\n", " B 75 113 122 0\n", " end A 126 15 138 28\n", " B 125 118 1 110" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df4 = DataFrame(data = np.random.randint(0,150,size = (12,4)),\n", " columns = [\"Spring\",'Summer','Autumn','Winter'],\n", " index = pd.MultiIndex.from_product([['张三','Sara','Lisa'],['middle','end'],list('AB')]))\n", "\n", "df4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "============================================\n", "\n", "练习8：\n", "\n", "1. 创建一个DataFrame，表示出张三李四期中期末各科成绩\n", "\n", "============================================" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. 多层列索引" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "除了行索引index，列索引columns也能用同样的方法创建多层索引" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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张三SaraLisa
middleendmiddleendmiddleend
ABABABABABAB
Spring1317142111972921391326314256
Summer10511812219171331003612020129136
Autumn10012132531095710412596687689
Winter73165442744812925563928113
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" ], "text/plain": [ " 张三 Sara Lisa \n", " middle end middle end middle end \n", " A B A B A B A B A B A B\n", "Spring 131 7 14 21 119 72 92 139 132 63 142 56\n", "Summer 105 118 122 19 17 133 100 36 120 20 129 136\n", "Autumn 100 121 32 53 109 57 104 125 96 68 76 89\n", "Winter 73 16 54 42 74 48 129 25 56 39 28 113" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df5 = DataFrame(data = np.random.randint(0,150,size = (4,12)),\n", " columns = pd.MultiIndex.from_product([['张三','Sara','Lisa'],['middle','end'],list('AB')]),\n", " index = [\"Spring\",'Summer','Autumn','Winter'])\n", "\n", "df5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. 多层索引对象的索引与切片操作" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1）Series的操作" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "【重要】对于Series来说，直接中括号[]与使用.loc()完全一样，因此，推荐使用中括号索引和切片。" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "张三 期中 40\n", " 期末 79\n", "李四 期中 88\n", " 期末 109\n", "Michael 期中 146\n", " 期末 51\n", "dtype: int64" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/plain": [ "张三 期中 40\n", " 期末 79\n", "李四 期中 88\n", " 期末 109\n", "静静 期中 146\n", " 期末 51\n", "dtype: int64" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#多层索引进行切片时，有些汉字，或者英文，不识别，运行异常，并不是代码的问题，自身的bug\n", "\n", "s.index = pd.MultiIndex.from_product([['张三','李四','静静'],['期中','期末']])\n", "s" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/plain": [ "张三 期中 40\n", " 期末 79\n", "李四 期中 88\n", " 期末 109\n", "dtype: int64" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s['张三':'李四']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(1) 索引" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "期中 40\n", "期末 79\n", "dtype: int64" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s['张三']" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "40" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s['张三','期中']" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": true }, "outputs": [ { "ename": "KeyError", "evalue": "'the label [期中] is not in the [index]'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1433\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontains\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1434\u001b[0;31m \u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1435\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1428\u001b[0m raise KeyError(\"the label [%s] is not in the [%s]\" %\n\u001b[0;32m-> 1429\u001b[0;31m (key, self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m 1430\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'the label [期中] is not in the [index]'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'期中'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1326\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1327\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply_if_callable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1328\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1329\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1330\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1549\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1550\u001b[0m \u001b[0;31m# fall thru to straight lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1551\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_valid_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1552\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1553\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1440\u001b[0m \u001b[0;32mraise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1441\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1442\u001b[0;31m \u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1443\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1444\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1427\u001b[0m \"key\")\n\u001b[1;32m 1428\u001b[0m raise KeyError(\"the label [%s] is not in the [%s]\" %\n\u001b[0;32m-> 1429\u001b[0;31m (key, self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m 1430\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1431\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'the label [期中] is not in the [index]'" ] } ], "source": [ "#多层索引，有层的概念\n", "s.loc['期中']" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "109" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s.loc['李四','期末']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(2) 切片" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "张三 期中 40\n", " 期末 79\n", "李四 期中 88\n", "dtype: int64" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s.iloc[0:3]" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": true }, "outputs": [ { "ename": "UnsortedIndexError", "evalue": "'Key length (1) was greater than MultiIndex lexsort depth (0)'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mUnsortedIndexError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'张三'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m'Michael'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/series.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 640\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_bool_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 641\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 642\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_with\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 643\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 644\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_get_with\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/series.py\u001b[0m in \u001b[0;36m_get_with\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 645\u001b[0m \u001b[0;31m# other: fancy integer or otherwise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 646\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m 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"\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m_convert_slice_indexer\u001b[0;34m(self, key, kind)\u001b[0m\n\u001b[1;32m 1405\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1406\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1407\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mslice_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1408\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1409\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_index_slice\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mslice_indexer\u001b[0;34m(self, start, end, step, kind)\u001b[0m\n\u001b[1;32m 3348\u001b[0m \"\"\"\n\u001b[1;32m 3349\u001b[0m start_slice, end_slice = self.slice_locs(start, end, step=step,\n\u001b[0;32m-> 3350\u001b[0;31m kind=kind)\n\u001b[0m\u001b[1;32m 3351\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3352\u001b[0m \u001b[0;31m# return a slice\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36mslice_locs\u001b[0;34m(self, start, end, step, kind)\u001b[0m\n\u001b[1;32m 1908\u001b[0m \u001b[0;31m# This function adds nothing to its parent implementation (the magic\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1909\u001b[0m \u001b[0;31m# happens in get_slice_bound method), but it adds meaningful doc.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1910\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mMultiIndex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mslice_locs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1911\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1912\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_partial_tup_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36m_partial_tup_index\u001b[0;34m(self, tup, side)\u001b[0m\n\u001b[1;32m 1915\u001b[0m \u001b[0;34m'Key length (%d) was greater than MultiIndex'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1916\u001b[0m \u001b[0;34m' lexsort depth (%d)'\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1917\u001b[0;31m (len(tup), self.lexsort_depth))\n\u001b[0m\u001b[1;32m 1918\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1919\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mUnsortedIndexError\u001b[0m: 'Key length (1) was greater than MultiIndex lexsort depth (0)'" ] } ], "source": [ "s['张三':'Michael']" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": true }, "outputs": [ { "ename": "UnsortedIndexError", "evalue": "'Key length (1) was greater than MultiIndex lexsort depth (0)'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mUnsortedIndexError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'张三'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m'Michael'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1326\u001b[0m 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kind=kind)\n\u001b[0m\u001b[1;32m 3351\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3352\u001b[0m \u001b[0;31m# return a slice\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36mslice_locs\u001b[0;34m(self, start, end, step, kind)\u001b[0m\n\u001b[1;32m 1908\u001b[0m \u001b[0;31m# This function adds nothing to its parent implementation (the magic\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1909\u001b[0m \u001b[0;31m# happens in get_slice_bound method), but it adds meaningful doc.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1910\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mMultiIndex\u001b[0m\u001b[0;34m,\u001b[0m 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"\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36mget_slice_bound\u001b[0;34m(self, label, side, kind)\u001b[0m\n\u001b[1;32m 1879\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1880\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1881\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_partial_tup_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mside\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mside\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1882\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1883\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mslice_locs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstart\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36m_partial_tup_index\u001b[0;34m(self, tup, side)\u001b[0m\n\u001b[1;32m 1915\u001b[0m \u001b[0;34m'Key length (%d) was greater than MultiIndex'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1916\u001b[0m \u001b[0;34m' lexsort depth (%d)'\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1917\u001b[0;31m (len(tup), self.lexsort_depth))\n\u001b[0m\u001b[1;32m 1918\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1919\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mUnsortedIndexError\u001b[0m: 'Key length (1) was greater than MultiIndex lexsort depth (0)'" ] } ], "source": [ "s.loc['张三':'Michael']" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "A e 46\n", " f 93\n", "B e 76\n", " f 77\n", "C e 61\n", " f 125\n", "dtype: int64" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s2 = Series(data = np.random.randint(0,150,size = 6),index = pd.MultiIndex.from_product([list('ABC'),['e','f']]))\n", "s2" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/plain": [ "A e 46\n", " f 93\n", "B e 76\n", " f 77\n", "C e 61\n", " f 125\n", "dtype: int64" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s2['A':'C']" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "A e 46\n", " f 93\n", "B e 76\n", " f 77\n", "dtype: int64" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s2.loc['A':'B']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2）DataFrame的操作" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(1) 可以直接使用列名称来进行列索引" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
张三期中315712434
期末134206055
李四期中337012847
期末955101117
Sara期中14114146147
期末1081147386
\n", "
" ], "text/plain": [ " Spring Summer Autumn Winter\n", "张三 期中 31 57 124 34\n", " 期末 134 20 60 55\n", "李四 期中 33 70 128 47\n", " 期末 9 55 101 117\n", "Sara 期中 14 114 146 147\n", " 期末 108 114 73 86" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "31" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3['Spring']['张三','期中']" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": true }, "outputs": [ { "ename": "KeyError", "evalue": "('Spring', '李四')", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2441\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2442\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2443\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5280)\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5126)\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20523)\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20477)\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: ('Spring', '李四')", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf3\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Spring'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'李四'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1962\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1963\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1964\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1965\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1966\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1969\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1970\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1971\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1972\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1973\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1643\u001b[0m \u001b[0mres\u001b[0m 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\u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3592\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2442\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2443\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2444\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2445\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2446\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5280)\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5126)\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20523)\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20477)\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: ('Spring', '李四')" ] } ], "source": [ "#DataFrame多层索引和之前索引类似\n", "#df [] 代表着列索引\n", "df3['Spring','李四']" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "A a 31 57 124 34\n", " b 134 20 60 55\n", "B a 33 70 128 47\n", " b 9 55 101 117\n", "C a 14 114 146 147\n", " b 108 114 73 86" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3.index = pd.MultiIndex.from_product([list('ABC'),list('ab')])\n", "df3" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
SpringSummerAutumnWinter
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "A a 31 57 124 34\n", " b 134 20 60 55\n", "B a 33 70 128 47\n", " b 9 55 101 117" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#使用切片\n", "df3['A':'B']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(2) 使用行索引需要用loc()等函数\n", "\n", "【极其重要】推荐使用loc()函数" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "注意在对行索引的时候，若一级行索引还有多个，对二级行索引会遇到问题！也就是说，无法直接对二级索引进行索引，必须让二级索引变成一级索引后才能对其进行索引！" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "a 31 57 124 34\n", "b 134 20 60 55" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3.loc['A']" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/plain": [ "Spring 33\n", "Summer 70\n", "Autumn 128\n", "Winter 47\n", "Name: (B, a), dtype: int64" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3.loc['B','a']" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": true }, "outputs": [ { "ename": "KeyError", "evalue": "'the label [a] is not in the [index]'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1433\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontains\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1434\u001b[0;31m \u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1435\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1428\u001b[0m raise KeyError(\"the label [%s] is not in the [%s]\" %\n\u001b[0;32m-> 1429\u001b[0;31m (key, self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m 1430\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'the label [a] is not in the [index]'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf3\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'a'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1326\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1327\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply_if_callable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1328\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1329\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1330\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1549\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1550\u001b[0m \u001b[0;31m# fall thru to straight lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1551\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_valid_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1552\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1553\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1440\u001b[0m \u001b[0;32mraise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1441\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1442\u001b[0;31m \u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1443\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1444\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1427\u001b[0m \"key\")\n\u001b[1;32m 1428\u001b[0m raise KeyError(\"the label [%s] is not in the [%s]\" %\n\u001b[0;32m-> 1429\u001b[0;31m (key, self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m 1430\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1431\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'the label [a] is not in the [index]'" ] } ], "source": [ "df3.loc['a']" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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SpringSummerAutumnWinter
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SpringSummerAutumnWinter
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "A a 31 57 124 34\n", " b 134 20 60 55\n", "B a 33 70 128 47\n", " b 9 55 101 117" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3.loc['A':'B']" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
SpringSummerAutumnWinter
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\n", "
" ], "text/plain": [ " Spring Summer Autumn Winter\n", "A a 31 57 124 34\n", " b 134 20 60 55\n", "B a 33 70 128 47" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3.iloc[0:3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "============================================\n", "\n", "练习9：\n", "\n", "1. 分析比较Series和DataFrame各种索引的方式，熟练掌握.loc()方法\n", "\n", "2. 假设张三再一次在期中考试的时候因为特殊原因放弃英语考试，如何实现？\n", "\n", "============================================" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## 4. 索引的堆（stack）" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- ``stack()``\n", "- ``unstack()``" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "小技巧】使用stack()的时候，level等于哪一个，哪一个就消失，出现在行里。" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " 张三 Sara Lisa \n", " middle end middle end middle end \n", " A B A B A B A B A B A B\n", "Spring 131 7 14 21 119 72 92 139 132 63 142 56\n", "Summer 105 118 122 19 17 133 100 36 120 20 129 136\n", "Autumn 100 121 32 53 109 57 104 125 96 68 76 89\n", "Winter 73 16 54 42 74 48 129 25 56 39 28 113" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df5" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " end middle \n", " A B A B\n", "Spring Lisa 142 56 132 63\n", " Sara 92 139 119 72\n", " 张三 14 21 131 7\n", "Summer Lisa 129 136 120 20\n", " Sara 100 36 17 133\n", " 张三 122 19 105 118\n", "Autumn Lisa 76 89 96 68\n", " Sara 104 125 109 57\n", " 张三 32 53 100 121\n", "Winter Lisa 28 113 56 39\n", " Sara 129 25 74 48\n", " 张三 54 42 73 16" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df5.stack(level = 0)" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Spring Summer Autumn Winter \n", " end middle end middle end middle end middle\n", "Lisa A 126 23 15 142 138 65 28 67\n", " B 125 75 118 113 1 122 110 0\n", "Sara A 9 111 8 90 97 9 0 128\n", " B 70 40 16 95 60 149 10 44\n", "张三 A 135 61 147 58 141 64 107 105\n", " B 97 118 29 121 31 8 56 81" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df4.unstack(level=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "【小技巧】使用unstack()的时候，level等于哪一个，哪一个就消失，出现在列里。" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "============================================\n", "\n", "练习10：\n", "\n", "1. 使用unstack()将ddd变为两行，分别为期中期末\n", "\n", "2. 使用unstack()将ddd变为四行，分别为四个科目\n", "\n", "============================================" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## 5. 聚合操作" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "【注意】\n", "\n", "- 需要指定axis\n", "\n", "- 【小技巧】和unstack()相反，聚合的时候，axis等于哪一个，哪一个就会进行计算。" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "所谓的聚合操作：平均数，方差，最大值，最小值……" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "A a 31 57 124 34\n", " b 134 20 60 55\n", "B a 33 70 128 47\n", " b 9 55 101 117\n", "C a 14 114 146 147\n", " b 108 114 73 86" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "A a 61.50\n", " b 67.25\n", "B a 69.50\n", " b 70.50\n", "C a 105.25\n", " b 95.25\n", "dtype: float64" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3.mean(axis = 'columns')" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Spring Summer Autumn Winter\n", "A a 31 57 124 34\n", " b 134 20 60 55\n", "B a 33 70 128 47\n", " b 9 55 101 117\n", "C a 14 114 146 147\n", " b 108 114 73 86" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df3" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "Spring 52.738664\n", "Summer 36.740532\n", "Autumn 33.571814\n", "Winter 44.086279\n", "dtype: float64" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#数据离散的程度，\n", "df3.std()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "============================================\n", "\n", "练习11：\n", "\n", "1. 计算各个科目期中期末平均成绩\n", "\n", "2. 计算各科目张三李四的最高分\n", "\n", "============================================" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 2 }