join on column pandas

1# df1 as main df and use the feild from df2 and map it into df1
2
3df1.merge(df2,on='columnName',how='left')

1pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')

1In [99]: result = left.join(right, on=['key1', 'key2'], how='inner')
2

1pd.merge(product,customer,on='Product_ID')

1# Joins with another DataFrame
2
3df.join(df2, df.name == df2.name, 'outer').select(
4  df.name, df2.height).collect()
5# [Row(name=None, height=80), Row(name=u'Bob', height=85), Row(
6#   name=u'Alice', height=None)]
7
8df.join(df2, 'name', 'outer').select('name', 'height').collect()
9# [Row(name=u'Tom', height=80), Row(name=u'Bob', height=85), Row(
10#   name=u'Alice', height=None)]
11
12cond = [df.name == df3.name, df.age == df3.age]
13df.join(df3, cond, 'outer').select(df.name, df3.age).collect()
14# [Row(name=u'Alice', age=2), Row(name=u'Bob', age=5)]
15
16df.join(df2, 'name').select(df.name, df2.height).collect()
17# Row(name=u'Bob', height=85)]
18
19df.join(df4, ['name', 'age']).select(df.name, df.age).collect()
20# [Row(name=u'Bob', age=5)]

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