Overview

== Python visualization library based on Matplotlib (Python’s core 2D plotting library)
– provides a high-level interface for the visualization of statistical data
– does not have its own graphics library, but uses the functionalities and data structures of Matplotlib internally

Dependencies

– Python 3.6
– numpy
– scipy
– pandas
– Matplotlib

Matplotlib vs. Seaborn

Matplotlib weaken:

– bad default options for size and color of plots
– Low level technology compared to today’s requirements, requiring very specialized code to generate appealing plots
– no development for Pandas Dataframes

Features

– Built-in themes for styling Matplotlib graphics
– Dataset-oriented API for determining the relationship between variables
– Visualization of univariate and bivariate data
– Automatic estimation and display of linear regression models
– Plotting of statistical time series data
– works well with NumPy and Pandas data structures
– It comes with integrated themes for styling matplotlib graphics

seaborn
Overview of Seaborn plotting functions

The product and further information can be found here:

https://seaborn.pydata.org/