Right Join
Another type of join is the right one. This join is literally the same as the left join, but with swapped tables (i.e., to perform a right join of table1 to table2 is literally the same as left join of table2 to table1). To perform a right join, set the how = 'right' parameter.
So both data1.merge(data2, on = 'id', how = 'right') and data2.merge(data1, on = 'id', how = 'left') will return the same result (with changed order of columns).
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# Importing library
import pandas as pd
# Loading data
data1 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data1.csv')
data2 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data2.csv')
# Perform a left join
df_res = data1.merge(data2, on = 'id', how = 'right')
print(df_res)
12345678910# Importing library import pandas as pd # Loading data data1 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data1.csv') data2 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data2.csv') # Perform a left join df_res = data1.merge(data2, on = 'id', how = 'right') print(df_res)
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Section 5. Chapitre 3
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