Answers for "join df"

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)

join to dataframes pandas

>>> df.join(other.set_index('key'), on='key')
  key   A    B
0  K0  A0   B0
1  K1  A1   B1
2  K2  A2   B2
3  K3  A3  NaN
4  K4  A4  NaN
5  K5  A5  NaN