Welcome to the Comprehensive Data Visualization Course repository by Muhammad Sheraz. This repository is your go-to resource for mastering the art of data visualization. Whether you're a beginner, a data enthusiast, or a professional in the field, this course is designed to enhance your skills and proficiency in creating impactful visualizations using various tools and techniques.
In this course, we will explore the principles of effective data visualization and dive into practical applications using popular visualization libraries and tools. From basic charts to interactive dashboards, you will learn how to communicate complex data insights in a visually compelling way.
- Introduction to Data Visualization
- Chart Chooser
- Anatomy of a Figure
- Download and Install Matplotlib
- How to Draw a Line Chart
- Enhance the Graph Step by Step
- Anatomy of a Figure (Recap)
- Recap of Line Chart
- Bar Plot
- Scatter Plot
- Recap: Anatomy of a Figure, Line, Bar, Scatter Chart
- Pie Chart
- Histogram
- Recap: Anatomy of a Figure, Line, Bar, Scatter Chart
- Box Plot
- Violin Plot
- Heatmap
- Subplots
- Overview of Seaborn Library
- Download and Install Seaborn
- Built-in Datasets of Seaborn Library
- Plotting with Seaborn
- The
relplot()
method - The
displot()
method - The
catplot()
method
- The
- Overview of Ploty Library
- Download and Install Ploty
- Built-in Datasets of Ploty Library
- Plotting with Ploty
- The
plot()
method - The
scatter()
method - The
bar()
method - The
histogram()
method - The
box()
method - The
heatmap()
method - The
surface()
method - The
choropleth()
method
- The
- Clone this repository to your local machine using
git clone
. - Navigate to the relevant lecture folders to access code, resources, and notes for each topic.
- Review the provided code examples and run them to understand the practical implementations.
- Apply the concepts learned to your own datasets and projects.
- Contribute, report issues, or suggest improvements to enhance the quality of this repository.
If you have questions, suggestions, or feedback, feel free to create an issue or reach out to me via email at [email protected].
I hope you find these lectures valuable in your journey to mastering data visualization. Create engaging visual stories with your data and make a significant impact in conveying insights effectively! ๐