Pandas中两个dataframe的交集和差集的示例代码
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2022-06-17 15:20:44
创建测试数据:import pandas as pdimport numpy as np #create a dataframedf1 = { 'subject':['semester1','sem...
创建测试数据:
import pandas as pd import numpy as np #create a dataframe df1 = { '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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