pandas DataFrame 交集并集补集的实现

2019-11-25 12:40:15

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1.场景，对于colums都相同的dataframe做过滤的时候

例如：

df1 = DataFrame([['a', 10, '男'],          ['b', 11, '男'],          ['c', 11, '女'],          ['a', 10, '女'],         ['c', 11, '男']],         columns=['name', 'age', 'sex'])df2 = DataFrame([['a', 10, '男'],          ['b', 11, '女']],        columns=['name', 'age', 'sex'])

取交集：print(pd.merge(df1,df2,on=['name', 'age', 'sex']))

取并集：print(pd.merge(df1,df2,on=['name', 'age', 'sex'], how='outer'))

取差集(从df1中过滤df1在df2中存在的行)：

df1 = df1.append(df2)df1 = df1.append(df2)df1 = df1.drop_duplicates(subset=['name', 'age', 'sex'],keep=False)print(df1)

代码：

# -*- coding:utf-8 -*-__version__ = '1.0.0.0'"""@brief :  简介@details:  详细信息@author :  zhphuang@date  :  2018-10-29"""import pandas as pdfrom pandas import *df1 = DataFrame([['a', 10, '男'],         ['b', 11, '男'],         ['c', 11, '女'],         ['a', 10, '女'],         ['c', 11, '男']],        columns=['name', 'age', 'sex'])print("df1:/n%s/n/n" % df1)df2 = DataFrame([['a', 10, '男'],         ['b', 11, '女']],        columns=['name', 'age', 'sex'])print("df2:/n%s/n/n" % df2)# 取交集print("交集:/n%s/n/n" % pd.merge(df1,df2,on=['name', 'age', 'sex']))# 取并集print("并集:/n%s/n/n" % pd.merge(df1,df2,on=['name', 'age', 'sex'], how='outer'))# 从df1中过滤df1在df2中存在的行，也就是取补集df1 = df1.append(df2)df1 = df1.append(df2)print("补集(从df1中过滤df1在df2中存在的行):/n%s/n/n" % df1.drop_duplicates(subset=['name', 'age', 'sex'],keep=False))

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