Data Visualization Projects
Libraries for visualizing data and creating charts.
3 projects available
How to Choose the Right Data Visualization Library for Python?
To choose among the most popular data visualization libraries: Matplotlib is ideal for creating static, animated, or interactive visualizations with detailed customization. Seaborn, built on Matplotlib, is best for creating statistically-oriented, more attractive graphics with less code, making complex visualizations easy and quick. Select Plotly for interactive, web-based visualizations that can be embedded in dashboards or websites, particularly useful when your data visualization needs to be dynamic and interactive for the end-user.
Weather Data Visualization with Matplotlib
beginnerCreate publication-quality visualizations using Matplotlib's powerful plotting capabilities. Learn to build custom charts, control plot aesthetics, create subplots, and export figures in multiple formats - the foundation of data visualization in Python.
E-commerce Sales Analysis with Seaborn
beginnerMaster statistical visualization with Seaborn's high-level interface. Learn to create attractive distribution plots, regression visualizations, and categorical comparisons with minimal code - perfect for rapid data exploration and analysis.
Interactive Customer Churn Dashboard with Plotly
intermediateBuild interactive, web-ready visualizations and dashboards using Plotly. Learn to create charts with hover tooltips, zoom capabilities, and dynamic filtering - essential for modern data storytelling and business intelligence applications.