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).


              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)

Tout était clair ?

Merci pour vos commentaires !

Section 5. Chapitre 3

Demandez à l'IA

Posez n'importe quelle question ou essayez l'une des questions suggérées pour commencer notre discussion

Contenu du cours

Data Manipulation using pandas

1. Preprocessing Data: Part I

What is Data Preprocessing?Types consistency Poor Data Presentation Manipulating Strings Challenge Replacing Specific Elements Simultaneous Replacement Challenge

2. Preprocessing Data: Part II

Logical Inconsistency Removing Rows Challenge Outliers Challenge Missing Values Filling NA values Challenge

3. Grouping Data

What is Grouping Data?Grouping in pandas [1/2]Challenge Grouping in pandas [2/2]Challenge Grouping by Several Columns Challenge

4. Aggregating and Visualizing Data

Advanced Aggregation [1/2]Challenge Advanced Aggregation [2/2]Challenge Histograms Challenge Bar and Scatter Plots Other Types of Graphs Challenge 1 Challenge 2

5. Joining Data

What is Joining Data?Left Join Right Join Inner Join Outer Join Concatenation

Right Join

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).


              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)

Tout était clair ?

Merci pour vos commentaires !

Section 5. Chapitre 3