python ioc_python数据处理相关操作——loc、ioc、ix选取数据

python数据处理相关操作——选取数据

iloc，loc，ix

import pandas as pd

from pandas import DataFrame

创建数据框

data = {'a':[11,22,33,44],

'b':['aa','bb','cc','dd'],

'c':[9,8,7,6],

'd':[1,2,3,4]

}

df = DataFrame(data)

df

a b c d 0 11 aa 9 1 1 22 bb 8 2 2 33 cc 7 3 3 44 dd 6 4

iloc：通过行/列号选取数据

df.iloc[0] #选取第0行数据

a 11

b aa

c 9

d 1

Name: 0, dtype: object

df.iloc[0:2] #选取多行

a b c d 0 11 aa 9 1 1 22 bb 8 2

df.iloc[:,[1]] #也可以按照列号选取某列 选取第2列

b 0 aa 1 bb 2 cc 3 dd

df.iloc[0:1,[1]] #可以按照行号选取某行某列 选取第0行 第2列

b 0 aa

df.iloc[0:2,[0,1]] #可以按照行号选取多行多列 选取第0~2行 第0～2列

a b 0 11 aa 1 22 bb

loc通过标签选取数据

df.loc[0] #选取第1行 因为第1行的行号是0所以和iloc效果相同

a 11

b aa

c 9

d 1

Name: 0, dtype: object

data = {'a':[11,22,33,44],

'b':['aa','bb','cc','dd'],

'c':[9,8,7,6],

'd':[1,2,3,4]

}

df1 = DataFrame(data,index = ['a','b','c','d'])

df1

a b c d a 11 aa 9 1 b 22 bb 8 2 c 33 cc 7 3 d 44 dd 6 4

df1.loc['b'] #选取第b行

a 22

b bb

c 8

d 2

Name: b, dtype: object

df1.loc['b':] #选取多行

a b c d b 22 bb 8 2 c 33 cc 7 3 d 44 dd 6 4

df1.loc[:,['a']] #通过标签选取某列

a a 11 b 22 c 33 d 44

df1.loc[:,['a','b']] #通过标签选取多列

a b a 11 aa b 22 bb c 33 cc d 44 dd

df1.loc['a',['b','c']] #通过标签选取某行某列

b aa

c 9

Name: a, dtype: object

按照条件选取数据

df1.loc[df1['a']==11] #通过单个条件选取数据

a b c d a 11 aa 9 1

df1.loc[(df1['a']==11)&(df1['d']==1)] #通过单多个条件选取数据

a b c d a 11 aa 9 1

ix 简单粗暴 混合使用

也就是说 ix把iloc和loc语法综合了，爱用哪个用哪个，不过会报个warning

df #再看下dataframe

a b c d 0 11 aa 9 1 1 22 bb 8 2 2 33 cc 7 3 3 44 dd 6 4

df.ix[1] #可以像iloc通过行号选取

/Users/anaconda/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning:

.ix is deprecated. Please use

.loc for label based indexing or

.iloc for positional indexing

See the documentation here:

http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#ix-indexer-is-deprecated

"""Entry point for launching an IPython kernel.

a 22

b bb

c 8

d 2

Name: 1, dtype: object

df1

a b c d a 11 aa 9 1 b 22 bb 8 2 c 33 cc 7 3 d 44 dd 6 4

df1.ix['a'] #可以像loc通过标签选取

/Users/anaconda/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning:

.ix is deprecated. Please use

.loc for label based indexing or

.iloc for positional indexing

See the documentation here:

http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#ix-indexer-is-deprecated

"""Entry point for launching an IPython kernel.

a 11

b aa

c 9

d 1

Name: a, dtype: object

df1.ix[3,3] #通过行号选取指定位置的数据

/Users/anaconda/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning:

.ix is deprecated. Please use

.loc for label based indexing or

.iloc for positional indexing

See the documentation here:

http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#ix-indexer-is-deprecated

"""Entry point for launching an IPython kernel.

/Users/anaconda/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py:961: FutureWarning:

.ix is deprecated. Please use

.loc for label based indexing or

.iloc for positional indexing

See the documentation here:

http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#ix-indexer-is-deprecated

return getattr(section, self.name)[new_key]

4

df1.ix['a','a'] #通过标签选取指定位置的数据

/Users/anaconda/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning:

.ix is deprecated. Please use

.loc for label based indexing or

.iloc for positional indexing

See the documentation here:

http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#ix-indexer-is-deprecated

"""Entry point for launching an IPython kernel.

11

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