Apps Development, Cloud Computing, Data Analytics

5 Mins Read

Supercharge Your Excel Experience by Using Python to Read and Write Excel Files


Excel is a powerful spreadsheet software application that has become an essential tool for individuals and businesses worldwide. It offers a versatile platform for organizing, analyzing, and visualizing data in a structured manner. Whether managing finances, tracking inventory, creating charts, or performing complex calculations, Excel provides a wide range of features to help you accomplish these tasks efficiently.

One of its drawbacks is Excel’s inability to manage vast amounts of data. When using Excel to conduct complex operations on many data entries, you may experience major performance problems, especially if your formulas and macros are not performance optimized.

Excel might take a lot of time if you have to complete repetitive tasks. For instance, you would have to manually access each Excel file and copy-paste the identical formulas each time you want to replicate an analysis across many Excel files weekly.

Automation of Excel workflows with Python can address these issues. An easy Python script that writes to an Excel file can be used to complete tasks like spreadsheet consolidation, data cleansing, and predictive modeling in minutes.

Excel users can use Python programmers to develop schedulers that execute the script automatically at predetermined intervals, significantly lowering the human involvement needed to do the same activity repeatedly.

This blog will demonstrate how to use the Openpyxl package to read and write Excel files with Python.

Introduction to Openpyxl

Users can read Excel files and write to them using the Python package known as Openpyxl.

Without opening an Excel program, this framework enables you to write functions, prepare spreadsheets, produce reports, and generate charts.

Additionally, Openpyxl enables users to simultaneously run the same analysis across several data sets while iterating across worksheets.

Since users only need to conduct the analysis on a single worksheet and can duplicate it as many times as necessary, this increases efficiency and enables the automation of Excel procedures.

Pioneers in Cloud Consulting & Migration Services

  • Reduced infrastructural costs
  • Accelerated application deployment
Get Started

Step-by-Step Guide

Step 1 – Install Openpyxl

Open your command prompt or Powershell and enter the following command to install Openpyxl:


As soon as the package is successfully installed, the following message ought to appear:


Step 2 – Read Excel Files in Python with Openpyxl

In this tutorial, we’ll use the Kaggle video game sales dataset. For the sake of this tutorial, our team preprocessed this dataset; you may download the updated version from this link. To import Excel into Python, follow these steps:

Loading the Workbook

Import the Openpyxl library, then load the workbook into Python after obtaining the dataset:


After loading the Excel file as a Python object, you must instruct the library to access a certain worksheet. Two strategies exist for doing this:

The first technique uses the following line of code to call the active worksheet, which is the first page in the workbook:


Alternatively, if you are familiar with the worksheet’s name, you can easily access it. In this lesson segment, the “vgsales” sheet will be used:


Now, let’s count how many rows and columns there are in this worksheet:


The above code should render the following output:


Now that we know the sheet’s dimensions Let’s learn how to read data from the workbook.

Step 3 – Reading Data From a Cell

Look at the sheet we downloaded just now and perform the commands as suggested.

You can enter the cell’s value as follows in Openpyxl to retrieve data from a particular cell:


Step 4 – Reading Data From Multiple Cells

What if we wanted to print every cell value in a spreadsheet row after learning to read data from a specific cell?

To accomplish this, you can use a “for loop” to iterate through each value in a certain row:


All values in the first row will be printed thanks to the code above.

Step to Write Excel Files with Openpyxl

Let’s learn how to write data to Excel files using Openpyxl

Step 1 –  Write to a Cell

With Openpyxl, you can write to a file in two different methods.

To start, you can open the cell with its key directly:


The row and column of the cell you want to write to can also be specified:


If you use Openpyxl to write to an Excel file, you must save your changes each time you do so for them to appear on the worksheet:


A permission issue will pop up when you try to save your worksheet while it is open. Before saving any changes, make sure to close the Excel document. After that, you can reopen it to ensure your worksheet has been updated.

In cell K1, you’ll see that a brand-new column called “Sum of Sales” has been added.

Step 2 – Create a New Column

Now, add up the total sales for each region and enter it in column K.

For the sales information in the first row, we’ll do this:


For the first game in the worksheet, you’ll see that cell K2 has the total sales calculated.

Step 3 – Append New Rows

Create a tuple with the values you want to add and write it to the sheet to add a new row to the workbook:


By printing the last row in the spreadsheet, you can verify that this data has been appended:


Step 4 –  Delete Rows

You may run the following piece of code to eliminate the new entry we just created:


The row number you want to delete is the first input to the delete_rows() method. The second input specifies how many rows need to be eliminated.


This course has covered the fundamentals of using the Openpyxl package to read and write Excel files in Python.

Python and Excel are strong data manipulation tools that can be used independently to create analytical reports, create mathematical calculations, and build predictive models.

When Excel and Python are combined, a company’s workflows can be streamlined while maintaining a user experience that everyone in the organization is comfortable with.

Drop a query if you have any questions regarding Openpyxl and we will get back to you quickly.

Making IT Networks Enterprise-ready – Cloud Management Services

  • Accelerated cloud migration
  • End-to-end view of the cloud environment
Get Started

About CloudThat

CloudThat is an official AWS (Amazon Web Services) Advanced Consulting Partner and Training partner, AWS Migration Partner, AWS Data and Analytics Partner, AWS DevOps Competency Partner, Amazon QuickSight Service Delivery Partner, AWS EKS Service Delivery Partner, and Microsoft Gold Partner, helping people develop knowledge of the cloud and help their businesses aim for higher goals using best-in-industry cloud computing practices and expertise. We are on a mission to build a robust cloud computing ecosystem by disseminating knowledge on technological intricacies within the cloud space. Our blogs, webinars, case studies, and white papers enable all the stakeholders in the cloud computing sphere.

To get started, go through our Consultancy page and Managed Services PackageCloudThat’s offerings.


1. Can Python be used to automate Excel?

ANS: – Python will automate repetitive Excel processes, including data entry and formatting, in this work. You can accomplish this by writing macros or scripts that run automatically or using Python to communicate directly with the Excel program.

2. Can Python read and write to an Excel file?

ANS: – Using the Openpyxl module, Python can read and write Excel files.

WRITTEN BY Sonam Kumari



    Click to Comment

Get The Most Out Of Us

Our support doesn't end here. We have monthly newsletters, study guides, practice questions, and more to assist you in upgrading your cloud career. Subscribe to get them all!