Mastering Data Visualization with Python

This course will help you draw meaningful knowledge from the data you have.

Three systems of data visualization in R are covered in this course:

A. Pandas    B. Matplotlib  C. Seaborn

A. Types of graphs covered in the course using the pandas package:

Time-series: Line Plot

Single Discrete Variable: Bar Plot, Pie Plot

Single Continuous Variable:  Histogram, Density or KDE Plot, Box-Whisker Plot 

Two Continuous Variable: Scatter Plot

Two Variable: One Continuous, One Discrete: Box-Whisker Plot

B. Types of graphs using Matplotlib library:

Time-series: Line Plot

Single Discrete Variable: Bar Plot, Pie Plot

Single Continuous Variable:  Histogram, Density or KDE Plot, Box-Whisker Plot 

Two Continuous Variable: Scatter Plot

In addition, we will cover subplots as well, where multiple axes can be plotted on a single figure.

C. Types of graphs using Seaborn library:

In this we will cover three broad categories of plots:

relplot (Relational Plots): Scatter Plot and Line Plot

displot (Distribution Plots): Histogram, KDE, ECDF and Rug Plots

catplot (Categorical Plots): Strip Plot, Swarm Plot, Box Plot, Violin Plot, Point Plot and Bar plot

In addition to these three categories, we will cover these three special kinds of plots: Joint Plot, Pair Plot and Linear Model Plot

In the end, we will discuss the customization of plots by creating themes based on the style, context, colour palette and font.