What you'll learn:
- Understand which plots are suitable for different types of data, ensuring you select the most effective visualization method for your analysis.
- Visualize data by creating various graphs using the pandas, matplotlib, and seaborn libraries, enhancing your ability to communicate data insights.
- Master data visualization techniques to draw meaningful knowledge from your data, making informed decisions based on clear visual representations.
- Learn to create time-series line plots, bar plots, pie plots, histograms, density or KDE plots, and box-whisker plots using the pandas package.
- Explore matplotlib library to create time-series line plots, bar plots, pie plots, histograms, density or KDE plots, box-whisker plots, and scatter plots.
- Master the seaborn library to create relational plots (scatter and line plots), distribution plots, and categorical plots (strip, swarm, box, violin, point etc)
- Customize your plots by creating themes based on style, context, color palette, and font to enhance the visual appeal and clarity of your visualizations.
- Enhance your resume with advanced data visualization skills using Python, making you a competitive candidate in data science and analytics fields.
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.
