This hands-on course teaches learners how to prepare, analyze, and visually interpret data using Python’s Seaborn library, with a focus on census datasets. Beginning with foundational setup—such as installing Anaconda, configuring Jupyter Notebook, and loading libraries—the course progresses into exploratory data analysis and practical visualization techniques.
Seaborn Python: Design & Customize Advanced Visualizations
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3 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Prepare and preprocess census datasets for exploratory data analysis.
Create scatter, violin, swarm, heatmap, and multivariate plots in Seaborn.
Enhance chart readability and interpret insights for data storytelling.
Skills you'll gain
Details to know
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Recently updated!
August 2025
Assessments
4 assignments
Taught in English
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There is 1 module in this course
This module deepens learners’ understanding of Seaborn by exploring advanced data visualization techniques. Learners will gain hands-on experience with conditional plotting using FacetGrid, creating custom plotting logic, handling pairwise relationships, and applying stylistic enhancements such as figure styles and color palettes. The module emphasizes clarity in complex data visualization through structured layouts and design customization, enabling learners to create informative, publication-quality plots.
What's included
10 videos1 reading4 assignments1 plugin
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