pandas dataframe drop函数

使用drop函数删除dataframe的某列或某行数据：

drop(labels, axis=0, level=None, inplace=False, errors='raise')
 
         --  axis为0时表示删除行，axis为1时表示删除列

常用参数如下： 

import pandas as pd
import numpy as np
 
data = {'Country':['China','US','Japan','EU','UK/Australia', 'UK/Netherland'],
'Number':[100, 150, 120, 90, 30, 2],
'Value': [1, 2, 3, 4, 5, 6],
'label': list('abcdef')}
 
df = pd.DataFrame(data)
print("df原数据:\n", df, '\n')
 
out:
df原数据:
          Country  Number  Value label
0          China     100      1     a
1             US     150      2     b
2          Japan     120      3     c
3             EU      90      4     d
4   UK/Australia      30      5     e
5  UK/Netherland       2      6     f

删除单列：

print(df.drop('Country', axis = 1))
 
out:
   Number  Value label
0     100      1     a
1     150      2     b
2     120      3     c
3      90      4     d
4      30      5     e
5       2      6     f

删除多列：

print(df.drop(['Country','Number'], axis = 1))
 
out:
   Value label
0      1     a
1      2     b
2      3     c
3      4     d
4      5     e
5      6     f

删除单行：

print(df.drop(labels = 1, axis = 0))
 
out:
         Country  Number  Value label
0          China     100      1     a
2          Japan     120      3     c
3             EU      90      4     d
4   UK/Australia      30      5     e
5  UK/Netherland       2      6     f

删除多行：

print(df.drop(labels = [1,2], axis = 0))
 
out:
         Country  Number  Value label
0          China     100      1     a
3             EU      90      4     d
4   UK/Australia      30      5     e
5  UK/Netherland       2      6     f

使用range函数删除连续多行：

print(df.drop(labels = range(1,3), axis = 0))
 
out:
         Country  Number  Value label
0          China     100      1     a
3             EU      90      4     d
4   UK/Australia      30      5     e
5  UK/Netherland       2      6     f

参考：Pandas:删除行、列---DataFram.drop() - 后来的后来123 - 博客园