Mastering Data Visualization with Python

Visualize data using pandas, matplotlib ans seaborn libraries for data analysis and data science

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

What you’ll learn

  • Understand what plots are suitable for a type of data you have.
  • Visualize data by creating various graphs using pandas, matplotlib and seaborn libraries.

Course Content

  • Introduction –> 6 lectures • 49min.
  • Getting Data and Using the Pandas Package to Plot –> 14 lectures • 1hr 17min.
  • Matplotlib Library for Plots –> 13 lectures • 1hr 41min.
  • Seaborn Library for Plots –> 21 lectures • 2hr 48min.
  • Python for Absolute Beginners –> 19 lectures • 2hr 52min.

Mastering Data Visualization with Python

Requirements

  • Some basic knowledge of Python is expected. However this course does include a quick overview of Python knowledge required for this course..

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.