1200字范文,内容丰富有趣,写作的好帮手!
1200字范文 > Pandas——ix vs loc vs iloc区别

Pandas——ix vs loc vs iloc区别

时间:2022-01-16 06:37:15

相关推荐

Pandas——ix vs loc vs iloc区别

Different Choices for Indexing

1. loc——通过行标签索引行数据

1.1loc[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'''

1.2loc[‘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]''''

1.4loc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'''

1.5loc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'''

1,6loc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'''

2.4iloc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'''

想学人工智能(Python、数据分析、机器学习、深度学习、推荐系统、强化学习),来公众号AI派看看吧!!

本内容不代表本网观点和政治立场,如有侵犯你的权益请联系我们处理。
网友评论
网友评论仅供其表达个人看法,并不表明网站立场。