Pandas Left Join Two Dataframes

Introduction

There are two methods to left join two dataframes in Pandas.

Method 1

We can use how='left' tells join() to left join two dataframes.

df_1.join(df_2, how=’left’)

Method 2

We can use how='left' tells merge() to left join two dataframes.

df_1.merge(df_2, how=’left’, left_index=True,right_index=True)

Sample Data

The following is the two dataframes to be left joined. 

import pandas as pd
# dataframe 1
df_1 = pd.DataFrame({'Brand': ['Tesla', 'Toyota','Tesla','Ford'], 
     'Location': ['CA', 'CA','NY','MA']},index=list('abcd'))
print("df_1: \n",df_1)

# dataframe 2
df_2 = pd.DataFrame({ 
    'Name': ['Jake', 'Jacob','John','Jess','James']},index=list('abdek'))
print("df_2 \n",df_2)
df_1: 
     Brand Location
a   Tesla       CA
b  Toyota       CA
c   Tesla       NY
d    Ford       MA

df_2 
     Name
a   Jake
b  Jacob
d   John
e   Jess
k  James

Method 1: Use join()

Use how='left' in join() to left join two dataframes.

# use how='left' in join() to left join two dataframes 
joined_dataframe=df_1.join(df_2,how='left')
print(joined_dataframe)
    Brand Location   Name
a   Tesla       CA   Jake
b  Toyota       CA  Jacob
c   Tesla       NY    NaN
d    Ford       MA   John

Method 2: Use merge()

Use how='left' in merge() to left join two dataframes. 

# use how='left' in merge() to left join two dataframes 
joined_dataframe=df_1.merge(df_2, how='left', left_index=True,right_index=True)
print(joined_dataframe)
    Brand Location   Name
a   Tesla       CA   Jake
b  Toyota       CA  Jacob
c   Tesla       NY    NaN
d    Ford       MA   John

Further Reading