MP4 | h264, 1280×720 | Lang: English | Audio: aac, 44100 Hz | 9h 26m | 3.85 GB
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
Requirements
Some basic knowledge of Python is expected. However this course does include a quick overview of Python knowledge required for this course.
Description
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.
Who this course is for:
Data Science, Six Sigma and other professionals interested in data visualization
Professionals interested in creating publication quality plots
Professionals who are not happy with the plots created in MS Excel, and see them as dull and boring
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