Example 1: 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'])
Example 2: join on column pandas
df1.merge(df2,on='columnName',how='left')
Example 3: pandas left join
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")
Example 4: joins in pandas
pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')
Example 5: joins in pandas
pd.merge(product,customer,on='Product_ID')
Example 6: 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)