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Effortlessly Add Rows in Excel with Openpyxl using Python

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Are you tired of manually adding rows in your Excel spreadsheets? Well, look no further because Openpyxl in Python has got you covered! With just a few lines of code, you can easily and effortlessly add rows to your Excel file. Say goodbye to the days of tedious copying and pasting.

This powerful and intuitive library allows you to automate Excel tasks and increase your productivity. Whether you’re working with large datasets or just need to add a few extra rows, Openpyxl makes it simple and straightforward. The best part? You don’t have to be a coding expert to use it!

In this article, we will guide you through the process of adding rows in Excel using Openpyxl in Python. We will cover everything from setting up your environment and installing the library to writing the code to add the rows. By the end of this article, you’ll be able to confidently tackle any Excel task with ease.

If you’re looking to streamline your Excel workflow and increase your efficiency, then this article is for you. Don’t let manual data entry slow you down. Let Openpyxl do the heavy lifting for you. So, what are you waiting for? Read on to discover how to effortlessly add rows in Excel with Openpyxl using Python!

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“Insert Row Into Excel Spreadsheet Using Openpyxl In Python” ~ bbaz


Microsoft Excel has been an incredibly popular tool for businesses, statisticians, accountants, and virtually any industry that utilizes data. Its functions are unmatched and a staple in almost every office environment. However, it can become tedious when there are hundreds or even thousands of rows of data. Many Python libraries have arisen to make data manipulation more efficient, and one such library is openpyxl.

What is Openpyxl?

Openpyxl is a Python library that allows users to manipulate and interact with Microsoft Excel files using Python. It not only facilitates the process of creating and editing Excel sheets but also allows for easy automation by allowing developers to read and write to JSON and CSV formats.

The Problem: Manually Adding Rows

Adding rows manually in Excel can be time-consuming and frustrating when dealing with large amounts of data. Now imagine having to do this for tens of thousands or even millions of rows. Openpyxl makes adding rows less complicated and less painstakingly manual.

Openpyxl Solution: Adding Rows with Ease

One of Openpyxl’s functions that make data management easier is its ability to add and insert rows into Excel spreadsheets. While you can certainly insert rows without using Openpyxl, it would require heavy coding knowledge and a significant amount of time.

Inserting Rows with Openpyxl

Here is a code snippet that shows how to insert a row in Openpyxl:

“`python#First, we import worksheets from the openpyxl libraryfrom openpyxl.worksheet import worksheet#We will then create a new worksheet and give it a namews = wb.create_sheet(My New Worksheet)#Next, we will select the row to insert the new row abovews.insert_rows(4)#Finally, we will populate the newly inserted row with datafor col, val in enumerate(header_values, start=1): ws.cell(row=4, column=col).value = val“`

The Result: Adding Rows with Openpyxl

The above code will create and rename a new worksheet My New Worksheet and adds a new row immediately below the header on line 4.

Comparing Openpyxl to Other Data Manipulation Libraries


Pandas is a data manipulation library that facilitates data analysis and data exploration in Python. While its functionalities closely align with what Openpyxl offers, the main difference between the two is how they interact with data.

Openpyxl is very specific to Excel interactions, while Pandas is more generalized but less efficient for Excel interactions. In addition, Pandas doesn’t allow users to preserve all of Excel’s functionality, such as formulae, parsing input, and formatting conditions that are used extensively in Excel. However, when it comes to handling large amounts of data, reading and writing to CSV or SQL databases, and creating complex visualizations, Pandas is the go-to option.


Numpy is another popular Python data manipulation library, but it is mainly used for mathematical computations and operations on arrays. Compared to Openpyxl, Numpy functions cannot interact with Excel sheets directly.

Openpyxl can be used in conjunction with Numpy, though, as openpyxl allows for reading and writing data from pandas DataFrames, which can be converted from and back to NumPy arrays.


In summary, Openpyxl is a great tool that makes managing and interacting with Excel sheets an easy task. It allows for quick and efficient manipulation of large data sets while preserving Excel’s fundamental features such as formulae and conditional formatting as well. While there are other data manipulation libraries for Python, Openpyxl is the obvious choice when working with Excel files specifically.

Thank you for visiting our blog and taking the time to read our article on adding rows to Excel with OpenPyXL using Python. We hope that you found the information provided helpful, informative and easy to follow.

We understand just how important it is to be able to efficiently manipulate data within Excel, and with OpenPyXL, we’re glad to say that it has never been easier. With its highly intuitive integration, you can automate the addition of rows without breaking a sweat.

As a closing message, we encourage you to explore more of what OpenPyXL has to offer. From dealing with charts, creating Pivot Tables and working with formulas, this library has got you covered. We look forward to seeing the wide range of applications you will discover!

People Also Ask: Effortlessly Add Rows in Excel with Openpyxl using Python

Here are some of the frequently asked questions about adding rows in Excel with Openpyxl using Python:

  1. What is Openpyxl?

    Openpyxl is a Python library that allows developers to read and write Excel files (XLSX/XLSM/XLSB/XLS) with Python. It is an open-source library that is easy to use and offers a lot of features for working with Excel files.

  2. How do I install Openpyxl?

    You can install Openpyxl using pip, which is the package installer for Python. Simply open your command prompt or terminal and type pip install openpyxl and press Enter. This will install the latest version of Openpyxl on your system.

  3. How do I add rows to an Excel file using Openpyxl?

    To add rows to an Excel file using Openpyxl, you need to first open the file using the load_workbook() method. Then, you can select the worksheet where you want to add the row using the active property. Finally, you can use the append() method of the worksheet object to add a new row to the end of the worksheet. Here’s an example:

                  import openpyxl                wb = openpyxl.load_workbook('example.xlsx')        ws =                # Add a new row        ws.append(['New Data'])                # Save the changes'example.xlsx')          
  4. Can I add multiple rows at once using Openpyxl?

    Yes, you can add multiple rows at once using Openpyxl. You just need to pass a list of lists to the append() method, where each inner list represents a row of data. Here’s an example:

                  import openpyxl                wb = openpyxl.load_workbook('example.xlsx')        ws =                # Add multiple rows        new_rows = [          ['New Data 1'],          ['New Data 2'],          ['New Data 3']        ]                for row in new_rows:          ws.append(row)                  # Save the changes'example.xlsx')          
  5. What if I want to add a row at a specific position in the worksheet?

    To add a row at a specific position in the worksheet, you can use the insert_rows() method of the worksheet object. This method takes two arguments: the row index where you want to insert the new row, and the number of rows to insert. Here’s an example:

                  import openpyxl                wb = openpyxl.load_workbook('example.xlsx')        ws =                # Insert a new row at index 3        ws.insert_rows(3, amount=1)                # Write data to the new row        ws.cell(row=3, column=1).value = 'New Data'                # Save the changes'example.xlsx')