In this article, we’ll be taking a look at one of the popular libraries of Python essential for data professionals, Pandas. You’d get to learn about its basics as well as its operations.

Let’s get started.

What is Pandas?

Python Pandas is popular for many reasons. Its primary application is data manipulation, its analysis as well as cleaning. You can use it for various data types and datasets, including unlabelled data, and ordered time-series data. To put it simply, we can say that Pandas is your data’s home. You can perform numerous operations on your data with this tool.

You can convert the data format of a file, merge two data sets, make calculations, visualize it by taking help from Matplotlib, etc. With so many functionalities, it’s a popular choice among data professionals. That’s why learning about it is essential. And without understanding its working, you can’t use it, so in this Python Pandas tutorial, we’ll be focusing on the same.

Read: Python Data Visualization Libraries

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