pandas left join
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")pandas left join
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")pd merge on multiple columns
new_df = pd.merge(A_df, B_df, how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])join on column pandas
# df1 as main df and use the feild from df2 and map it into df1
df1.merge(df2,on='columnName',how='left')joins in pandas
pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')joins in pandas
pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])join in pandas
import pandas as pd
clients = {'Client_ID': [111,222,333,444,555],
'Client_Name': ['Jon Snow','Maria Green', 'Bill Jones','Rick Lee','Pamela Lopez']
}
df1 = pd.DataFrame(clients, columns= ['Client_ID','Client_Name'])
countries = {'Client_ID': [111,222,333,444,777],
'Client_Country': ['UK','Canada','Spain','China','Brazil']
}
df2 = pd.DataFrame(countries, columns= ['Client_ID', 'Client_Country'])
Inner_Join = pd.merge(df1, df2, how='inner', on=['Client_ID', 'Client_ID'])
print(Inner_Join)Copyright © 2021 Codeinu
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