Matplotlib

This repository contains structured Jupyter notebooks and visual examples for learning and practicing Matplotlib, the most widely-used Python library for data visualization.

📁 Folder Structure

• 1_intro.ipynb – A basic introduction to Matplotlib, covering plot creation and rendering using pyplot.
• 2_Pyplot.ipynb – Hands-on with the pyplot interface: plotting lists, titles, labels, and grids.
• 3_Pyplot_Functions.ipynb – Styling plots using colors, markers, line styles, legends, limits, and ticks.
• 4_Data_Visualization.ipynb – Covers bar charts, horizontal bars, histograms, pie charts, and scatter plots.
• 5_Subplots&LayoutAdjustments.ipynb – Using subplots, layout adjustments, and multiple axes.
• 6_SavingFigures.ipynb – Demonstrates how to save plots to files in various formats with high DPI.

📄 Notebooks and Media

The repository includes Jupyter notebooks and exported image files generated from visualizations.

• line_plot.png – Example line plot generated from sales or trend data.
• Subplots.png – Combined subplot example showing multiple visualizations in one figure.

📊 Project Details

• netflix_titles.csv – Netflix dataset used for real-world analysis and visualizations.
• Project.ipynb – Full end-to-end Matplotlib project analyzing Netflix content using bar plots, pie charts, histograms, line plots, and scatter plots. Includes data cleaning, plotting, and saving figures.

📌 Goal

To build a comprehensive understanding of Matplotlib’s plotting capabilities and apply them to real datasets like Netflix, enhancing your data storytelling skills in Python.