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.
- Line Graphs and Time Series.
- Scatter Plots and Correlations.
- Bar Plots, Histograms, and Distributions.
- Pandas Visualizations and Grid Charts.
- Relational Plots and Multiple Variables.
- 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.