Join In Python

Join in Pandas

In Pandas, we can join or merge two data frames by using the merge() function. We can perform natural, left, right, and outer join in Pandas. We’ll further study these in this blog. Let us look at the syntax of how to join two data frames.

Syntax-

merge(df1,df2, on =’ID’, how=’type_of_join’)

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First of all, Let us create Dataframe

import pandas as pd
import numpy as np
d1 = {'Student_id':pd.Series([1,2,3,4,5,6]),
  'Names':pd.Series(['Aman ',' Raghav' ,'Rahul','Shubh','Usha','Surbhi'])}
df1 = pd.DataFrame(d1)
d2 = {'Student_id':pd.Series([2,4,6,7,8]),
    'Residence':pd.Series(['New York','New York','Texas','Singapore','Indiana'])}
df2 = pd.DataFrame(d2)

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Inner Join 

Inner Join returns only those rows in which the left table has matching keys in the right table.

The syntax of the same is-

pd.merge(df1, df2, on='Student_id', how='inner')

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After we run this code, the following output appears-

Outer Join

Outer Join in Pandas returns all the rows from both tables. It displays join records on the left side with matching keys in the right table. If no match exists from any table NaN will be returned.

The syntax of the same is-

pd.merge(df1, df2, on='Student_id', how='outer').

You can also try this code with Online Python Compiler

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After we run this code, the following output appears-

Left Outer Join 

Left Outer Join in Pandas returns all rows from the left table and the rows with matching keys from the right table. When there is no Matching from the right table, NaN will be returned.

The syntax of the same is-

pd. merge(df1, df2, on='Student_id', how='left')

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The resultant data frame will be

Right Outer Join

Right Outer Join returns all rows from the right table. It also returns any rows with matching keys from the left table.

The syntax of the same is-

pd. merge(df1, df2, on='Student_id', how='right') 

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The resultant data frame will be

Frequently Asked Questions 

What is Join in Python?

Join in Python is an inbuilt string function. It is used to join sequence elements separated by a string separator. The job of the merge function is to join the elements of a sequence and makes it a string. 

What do you mean by a Dataframe?

A Dataframe is a data structure that categorizes data into a 2-dimensional table of rows and columns. Dataframes are one of the most common data structures used in modern data analytics.

How many joins can we perform in Pandas?

We can perform natural, left, right, and outer join in Pandas.

State the difference between Left Outer Join and Right Outer Join.

Left Outer Join in Pandas returns all rows from the left table and the rows with matching keys from the right table. Right, Outer Join returns all rows from the right table. It also returns any rows with matching keys from the left table.

What is returned if there is no match found in the table?

If no match exists from any table, NaN will be returned.

Conclusion

This blog covered the Join in python. It introduced the concept of join in Pandas and explained the different types of Join in Python. We hope you are clear with this topic of Join in Python. Eager to learn more? Refer to our other blogs-

• getattr function in Python
• Anagram in Python
• Deque in Python

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