Answers for "pandas joins"

4

pandas left join

df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")
Posted by: Guest on November-26-2020
7

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'])
Posted by: Guest on March-26-2020
7

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')
Posted by: Guest on May-15-2020
5

joins in pandas

pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')
Posted by: Guest on May-31-2020
2

joins in pandas

pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])
Posted by: Guest on May-31-2020
1

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)
Posted by: Guest on March-30-2020

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