python数据处理相关操作——iloc、loc、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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