python库学习笔记——Pandas数据索引：ix、loc、iloc区别

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Different Choices for Indexing

1. loc——通过行标签索引行数据

1.1 loc[1]表示索引的是第1行（index 是整数）

import pandas as pddata = [[1,2,3],[4,5,6]]index = [0,1]columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc[1]'''a    4b    5c    6'''

1.2 loc[‘d’]表示索引的是第’d’行（index 是字符）

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc['d']'''a    1b    2c    3'''

1.3 如果想索引列数据，像这样做会报错

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc['a']'''KeyError: 'the label [a] is not in the [index]''''

1.4 loc可以获取多行数据

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc['d':]'''   a  b  cd  1  2  3e  4  5  6'''

1.5 loc扩展——索引某行某列

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc['d',['b','c']]'''b    2c    3'''

1,6 loc扩展——索引某列

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc[:,['c']]'''   cd  3e  6'''

当然获取某列数据最直接的方式是df.[列标签]，但是当列标签未知时可以通过这种方式获取列数据。

需要注意的是，dataframe的索引[1:3]是包含1,2,3的，与平时的不同。

2. iloc——通过行号获取行数据

2.1 想要获取哪一行就输入该行数字

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.loc[1]'''a    4b    5c    6'''

2.2 通过行标签索引会报错

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.iloc['a']'''TypeError: cannot do label indexing on <class 'pandas.core.index.Index'> with these indexers [a] of <type 'str'>'''

2.3 同样通过行号可以索引多行

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.iloc[0:]'''   a  b  cd  1  2  3e  4  5  6'''

2.4 iloc索引列数据

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.iloc[:,[1]]'''   bd  2e  5'''

3. ix——结合前两种的混合索引

3.1 通过行号索引

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.ix[1]'''a    4b    5c    6'''

3.2 通过行标签索引

import pandas as pddata = [[1,2,3],[4,5,6]]index = ['d','e']columns=['a','b','c']df = pd.DataFrame(data=data, index=index, columns=columns)print df.ix['e']'''a    4b    5c    6'''

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