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Pandas Tutorial- How to run analysis using Pandas Python

pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

Pandas is built on top of the NumPy package, meaning a lot of the structure of NumPy is used or replicated in Pandas. Data in pandas is often used to feed statistical analysis in SciPy, plotting functions from Matplotlib, and machine learning algorithms in Scikit-learn.

Pandas First Steps

Install and import

Pandas is an easy package to install. Open up your terminal program (for Mac users) or command line (for PC users) and install it using either of the following commands:

conda install pandas

OR

pip install pandas

Alternatively, if you’re currently viewing this article in a Jupyter notebook you can run this cell:

!pip install pandas

The ! at the beginning runs cells as if they were in a terminal.

To import pandas we usually import it with a shorter name since it’s used so much:






















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