创建测试数据：

import pandas as pdimport numpy as np #Create a DataFramedf1 = { 'Subject':['semester1','semester2','semester3','semester4','semester1', 'semester2','semester3'], 'Score':[62,47,55,74,31,77,85]} df2 = { 'Subject':['semester1','semester2','semester3','semester4'], 'Score':[90,47,85,74]} df1 = pd.DataFrame(df1,columns=['Subject','Score'])df2 = pd.DataFrame(df2,columns=['Subject','Score']) print(df1)print(df2)

运行结果：

求两个dataframe的交集

intersected_df = pd.merge(df1, df2, how='inner')print(intersected_df)

也可以指定求交集的列：

intersected_df = pd.merge(df1, df2, on=['Subject'], how='inner')print(intersected_df)

求差集

df2-df1：

set_diff_df = pd.concat([df2, df1, df1]).drop_duplicates(keep=False)print(set_diff_df)

df1-df2：

set_diff_df = pd.concat([df1, df2, df2]).drop_duplicates(keep=False)print(set_diff_df)

另一种求差集的方法是：

以df1-df2为例：

df1 = df1.append(df2)df1 = df1.append(df2)set_diff_df = df1.drop_duplicates(subset=['Subject', 'Score'],keep=False)print(set_diff_df)

得到的df1-df2结果是一样的：

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