Pandas is one of the most fundamental Python libraries for Data Science and Analysis on tabular data. It is an open-source library that provides numerous functionalities for various operations involving the preprocessing, analysis, and manipulation of tabular data with high speed and performance. It was developed by Wes McKinney in 2008. Python Pandas is the backbone of most data analytics and Machine Learning projects, having applications in various domains, such as statistics, finance, sales, and market research, etc.
The simplest way of installing and working with Pandas is using Anaconda. Anaconda is a cross-platform (Windows, Linux, Mac) Python distribution for scientific computing, data processing, and analysis. The greatest advantage is that it will also give access to various other tools and packages. If you don’t have Anaconda Navigator on your system you can install from https://www.anaconda.com, on whichever system you are using (i.e., Windows, Linux, Mac, etc.)
The user can then install the packages in anaconda, or can simply open up the terminal or command line and enter the command:
conda install pandas
pip install pandas
sudo pip install pandas
sudo pip install pandas
This is the introductory article on pandas and its installation. In upcoming article, we will focus on more detailed operations in pandas.
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