Last updated on September 13th, 2022 at 09:41 am

A Python Guide For An Excel Person

The most widely used programming language today, Python, has countless uses in various industries. It is the best option in terms of deployment and maintenance, thanks to its dynamic and flexible capabilities. MS Excel is one of the well-known Microsoft programs that functions like a spreadsheet and is used to store and analyze numerical data. 

It was among the first tools businesses worldwide used to evaluate data and draw conclusions. The phrase "conventional BI tool" is also used to describe it. You may easily transmit data from any source to any destination by using Python Excel Automation. 

Using Excel and Python for Data Science

In the year 1987, Microsoft created the spreadsheet program known as Excel. Almost all operating systems, including Windows, Android, etc., formally support it. It already has the Windows OS pre-installed and is simple to connect with other systems. Microsoft Excel is the most powerful and widely used application for working with structured data. 

Your data is arranged, processed, and stored in a tabular row-column format. Calculations, pivot tables, graphs, and much more are all possible! Since its introduction, this program has grown in popularity and is used extensively around the globe in various application sectors and domains. 

How Can Python Automate an Excel Spreadsheet?

Step 1: Analyze the datasheet 

Analyzing the Dataset is the first stage in Python Excel Automation. This lesson makes use of a sales dataset.

Step 2: Using Pandas to create pivot tables

Designing pivot tables is the next step in Python Excel Automation. Pandas often read an excel file, which generates the pivot table and exports it to Excel. Then, you can create charts and spreadsheets in Python and write Excel formulae using the Openpyxl module.

Step 3: Using Openpyxl to design the Reports

Designing the reports is the next phase in Python Excel Automation. You must use the "load workbook" function from Openpyxl to create the report, and you can save using the ".save()" method.

Step 4: Using Python to automate the report

The automation of your report is the next Python Excel Automation step. To make it simple to automate the report, you may write all the code in a single function. 

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