joins in pandas

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showing results for - "joins in pandas"
Dorothy
01 Apr 2019
1# df1 as main df and use the feild from df2 and map it into df1
2
3df1.merge(df2,on='columnName',how='left')
Jean-Baptiste
06 Mar 2019
1pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')
Maite
19 Jun 2016
1In [99]: result = left.join(right, on=['key1', 'key2'], how='inner')
2
Ade
26 Aug 2018
1pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])
Abril
11 Oct 2018
1import pandas as pd
2
3clients = {'Client_ID': [111,222,333,444,555],
4           'Client_Name': ['Jon Snow','Maria Green', 'Bill Jones','Rick Lee','Pamela Lopez']
5           }
6df1 = pd.DataFrame(clients, columns= ['Client_ID','Client_Name'])
7
8
9countries = {'Client_ID': [111,222,333,444,777],
10             'Client_Country': ['UK','Canada','Spain','China','Brazil']
11             }
12df2 = pd.DataFrame(countries, columns= ['Client_ID', 'Client_Country'])
13
14
15Inner_Join = pd.merge(df1, df2, how='inner', on=['Client_ID', 'Client_ID'])
16print(Inner_Join)
17
Audrey
18 Mar 2019
1pd.merge(product,customer,on='Product_ID')
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