Answers for "joins in pandas"

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')

join tables pandas

In [99]: result = left.join(right, on=['key1', 'key2'], how='inner')

joins in pandas

pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])

joins in pandas

pd.merge(product,customer,on='Product_ID')

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)