【Python】使用Pandas进行Excel多表外连接(outer join)

源代码

import pandas as pd
#读入.xlsx类型Excel文件
df1= pd.read_excel('C:/Users/Kinglake/Desktop/1.xlsx')
df2 = pd.read_excel('C:/Users/Kinglake/Desktop/2.xlsx')
#读入.csv类型Excel文件
df3 = pd.read_csv('C:/Users/Kinglake/Desktop/3.csv')#多表连接并导出excel(ignore_index=True使索引不会混乱)(.fillna(0)用0替换所有空单元格)
pd.concat([df1,df2,df3,df4,df5,df6],join='outer',ignore_index=True).fillna(0).to_excel("C:/Users/Kinglake/Desktop/output.xlsx")

节省内存的尝试

#节省内存的尝试
import pandas as pd
df1= pd.read_csv('/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/The-country01-level-6.csv')
df2 = pd.read_csv('/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/The-country02-level-6.csv')
temp1=pd.concat([df1,df2],join='outer',ignore_index=True)
del df1,dl2
df3 = pd.read_csv('/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/The-country03-level-6.csv')
df4 = pd.read_csv('/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/Thecountry04-level-6.csv')
temp2=pd.concat([df3,df4],join='outer',ignore_index=True)
del df3,dl4
df5 = pd.read_csv('/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/Thecountry05-level-6.csv')
df6 = pd.read_csv('/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/Thecountry06-level-6.csv')
temp3=pd.concat([df5,df6],join='outer',ignore_index=True)
del df5,dl6
temp4=pd.concat([temp1,temp2],join='outer',ignore_index=True)
del temp1,temp2
pd.concat([temp3,temp4],join='outer',ignore_index=True).fillna(0).to_excel("/home/ubuntu/Downloads/Thecountry-eachlevel/Thecountry-level-6/output6.xlsx")

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