Join Two DataFrames With Pandas Using Merge

Python

Data Preprocessing

In this code snippet we show 4 ways to merge or join two dataframes using the merge function that performs an inner join, left outer join, right outer join and full outer join.

 1|  # inner join
 2|  df = df1.merge(df2, left_on='col_A', right_on='col_B')
 3|  
 4|  # left outer join
 5|  df = df1.merge(df2, left_on='col_A', right_on='col_B', how='left')
 6|  
 7|  # right outer join
 8|  df = df1.merge(df2, left_on='col_A', right_on='col_B', how='right')
 9|  
10|  # full outer join
11|  df = df1.merge(df2, left_on='col_A', right_on='col_B', how='outer')
12|  
13|  # inner join where we want to join on col_A which is present in df1 
14|  # and df2
15|  df = df1.merge(df2, on='col_A')

DETRO

1 Upvote

Tags: Join | Merge

Did you find this snippet useful?

Sign up to bookmark this in your snippet library

Normalize Windowed Time Series

Python

Data Preprocessing

Scaler | Normalize | Scale | Min-max

4

Convert All Non-numeric Columns to Category Data Types

Python

Data Preprocessing

4

Creating a Running Total Column in Pandas

Python

Data Preprocessing

3

Pivoting Pandas Dataframes

Python

Data Preprocessing

3

Renaming Columns in a Pandas Dataframe Using Dictionaries & Lists

Python

Data Preprocessing

2

How to Remove Punctuation From Text with Python

Python

Data Preprocessing

Nlp | String | Punctuation

2

How To Set First Row of a Pandas Dataframe as Column Headers

Python

Data Preprocessing

2

How to Create Different Aggregations Using GroupBy, Agg & Dictionaries

Python

Data Preprocessing

2

Using Pandas GroupBy Transform Function

Python

Data Preprocessing

Transform | Groupby

2

Extract Date & Time Features From a Pandas Date Column

Python

Data Preprocessing

2