pandas dataframe drop函数介绍

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

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