Seaborn Library for Data Visualization in Python: Part 1
Introduction
In the previous article, we looked at how Python’s Matplotlib library can be used for data visualization. In this article we will look at Seaborn which is another extremely useful library for data visualization in Python. The Seaborn library is built on top of Matplotlib and offers many advanced data visualization capabilities.
Though, the Seaborn library can be used to draw a variety of charts such as matrix plots, grid plots, regression plots etc., in this article we will see how the Seaborn library can be used to draw distributional and categorial plots. In the second part of the series, we will see how to draw regression plots, matrix plots, and grid plots.
Downloading the Seaborn Library
The seaborn library can be downloaded in a couple of ways. If you are using pip installer for Python libraries, you can execute the following command to download the library:
pip install seaborn
Alternatively, if you are using the Anaconda distribution of Python, you can use execute the following command to download the seaborn library:
conda install seaborn
The Dataset
The dataset that we