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Joining two Pandas DataFrames using merge()

Joining Excel Data from Multiple files using Python Pandas

Last Updated : 17 Aug, 2020

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Let us see how to join the data of two excel files and save the merged data as a new Excel file.

We have 2 files, registration details.xlsx and exam results.xlsx.

registration details.xlsx

We are having 7 columns in this file with 14 unique students details. Column names are as follows :

Admission Date
Name of Student
Gender
DOB
Student email Id
Enquiry No.
Registration No.

exam results.xlsx

We are having 7 columns in this file with 32 unique students’ details. Column names are as follows :

Registration No.
Name
No.of questions attempted
Correct
Incorrect
Marks Obtained
Percentage

You can download these files from these links : registration details.xlsx and exam results.xlsx.

Now, let’s see the common columns between these two files :

So the common column between the excel files is REGISTRATION NO. So we need to merge these two files in such a way that the new excel file will only hold the required columns i.e. :

Algorithm :

Import the Pandas module.
Read both the files using the read_excel() function.
Combine them using the merge() function.
Use the to_excel() function, to create the resultant file.

   # importing the module 
import pandas 
  
# reading the files 
f1 = pandas.read_excel("registration details.xlsx") 
f2 = pandas.read_excel("exam results.xlsx") 
  
# merging the files 
f3 = f1[["REGISTRATION NO",  
         "STUDENT EMAIL ID "]].merge(f2[["REGISTRATION NO",  
                                         "Name", "Marks Obtained",  
                                         "Percentage"]],  
                                     on = "REGISTRATION NO",  
                                     how = "left") 
  
# creating a new file 
f3.to_excel("Results.xlsx", index = False) 
 
  

Output :

Joining two Pandas DataFrames using merge()

amitkkumra

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Article Tags :

Pandas
Python
Python-pandas

Practice Tags :

python

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