Pandas中两个dataframe的交集和差集的示例代码
(编辑：jimmy 日期: 2024/9/21 浏览：2)
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：
