This repository contains examples of data visualization using Seaborn and Matplotlib libraries. I've created various charts and plots showcasing the capabilities of these powerful tools on inbuilt datasets.
- Bar Charts: Explore different variations of bar charts to represent categorical data effectively.
- Line Plots: Visualize trends and patterns with line plots for time-series or continuous data.
- Scatter Plots: Analyze relationships and correlations between variables using scatter plots.
- Heatmaps: Gain insights into data patterns and relationships through color-coded heatmaps.
- Histograms and Distributions: Understand data distributions using histograms and kernel density plots.
- Box Plots: Identify statistical measures and outliers with box plots.
Each Python script in the repository corresponds to a specific type of chart. Simply run the scripts to generate the visualizations and customize them for your specific needs.
Feel free to explore, modify, and use these examples for your projects. Happy coding!
Note: Make sure you have Seaborn and Matplotlib installed in your Python environment.