Learn how to read and import Excel files in Python, write data to these spreadsheets, and find the best packages to do this.

Using Python And Excel For Data Science

Excel is a spreadsheet application that was developed by Microsoft in the Year 1987. It is officially supported by almost all of the operating systems like Windows, Macintosh, Android, etc. It comes pre-installed with the Windows OS and can be easily integrated with other OS platforms. Microsoft Excel is the best and the most accessible tool when it comes to working with structured data.

It organizes, analyzes, and stores your data in tabular row-column fashion. You can perform calculations and create pivot tables, graphs, and a lot more! Since its release, this software gained popularity and is widely used in many different application fields and all sorts of domains across the world.

Since the day internet was created, it has grown exponentially, and so has the amount of data. The growth in data has pushed the need for people to understand how to analyze it. Corporations and governments were collecting big data. Hence, the term data science was coined.

When working with data, you’ll need to deal with spreadsheets at some point; however, working directly with spreadsheets can get annoying at times, especially when you are a developer. To get rid of this problem, Python developers came up with ways of reading, writing, analyzing all kinds of file formats, including spreadsheets.

Today’s tutorial will be mostly on how you can use the Python programming language and work with Excel without directly using the Microsoft Excel application. It will provide you hands-on experience with the packages that you can use to load, read, write, and analyze these spreadsheets with the help of Python. You will be dealing with packages like pandas, openpyxl, xlrd, xlutils, and pyexcel.

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