In this course, you’ll learn the fundamentals of data visualization in Python by striking a good balance between graph interpretation via statistics and tooling in Matplotlib and Seaborn. Throughout this course, you’ll learn the most common methods and techniques to visualize data using a variety of Python libraries. At the end of the course, you’ll synthesize and apply this knowledge by completing a data visualization portfolio project.

This course focuses on the following:

• Developing fundamental knowledge of data visualization using Python libraries.
• Building proficiency in visualizing data with line plots, scatter plots, bar plots, and more.
• Optimizing your data visualization workflow to reveal insights and fuel data-driven action.

The Program

1. Line Graphs and Time Series.
2. Scatter Plots and Correlations.
3. Bar Plots, Histograms, and Distributions.
4. Pandas Visualizations and Grid Charts.
5. Relational Plots and Multiple Variables.
6. Guided Project: Finding Heavy Traffic Indicators on I-94.

What will you learn

• How to visualize time series data with line plots.
• How to visualize frequency distributions with bar plots and histograms.
• How to visualize multiple variables using Seaborn’s relational plots.
• How to define correlations and visualize them with scatter plots.
• How to improve your exploratory data visualization workflow using Pandas.