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Aprenda Outer Join | Joining Data
Data Manipulation using pandas

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Outer Join

Let's learn the last type of join - outer join. As you remember, left join keeps all the records from the left table, inner join keeps only records with matching values for both tables. Outer join performs almost an opposite action compared to inner join - it keeps all the records from both tables, and adds data if there are matches.

For instance, we can perform an outer join of the same two tables we used before.

# 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 = 'outer')
print(df_res)
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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 = 'outer') print(df_res)
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Seção 5. Capítulo 5
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