🎨 Visualizing Data — The Matplotlib Way 📈

A hands-on journey through Matplotlib, turning raw data into insightful and visually appealing plots — the heart of data visualization in Python.

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🧠 Tech Stack Badges

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🧩 Mission Statement

This repository serves as my personal Matplotlib Lab 🧪 where I experiment, learn, and practice data visualization techniques.

Each notebook is a step toward mastering plotting fundamentals, customizing visuals, and real-world data storytelling using Python.

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📂 Folder Structure

💡 Each folder inside the Matplotlib directory explores a unique aspect of Matplotlib — from basic plots to advanced visualization techniques.

matplotlib-lab/
│
└── Matplotlib/
    ├── Basic Matplotlib/
    │   ├── 2D_line_plot.ipynb
    │   ├── Bar_Chart.ipynb
    |   ├── Pie_chart.ipynb
    │   ├── Histogram.ipynb
    │   ├── Scatter_Plots.ipynb
    │   ├── barchart.jpg
    │   ├── line graph.png
    │   ├── sample_histogram.png
    │   ├── scatter-plot.png
    │   ├── pie-chart.svg
    │   └── histogram.svg
    │
    ├── Advanced/
    │   ├── Advanced_Scatter_Plots.ipynb
    │   ├── Subplots.ipynb
    │   ├── 3d_graphs_plotting.ipynb
    │   ├── heatmap.ipynb
    │   └── Pandas_plot.ipynb
    │
    └── Datasets/
        ├── IPL_Ball_by_Ball_2008_2022.csv
        ├── batsman_season_record.csv
        ├── batter.csv
        ├── gayle-175.csv
        ├── sharma-kohli.csv
        ├── vk.csv
        ├── iris.csv
        └── big-array.npy

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🧮 Topics Covered

🔹 Basic Plots

Notebook	Description
2D_line_plot.ipynb	Introduction to line graphs, axis labels, markers, and styles.
Bar_Chart.ipynb	Creating vertical & horizontal bar charts with customization.
Pie_chart.ipynb	Making pie charts with labels, percentages, and explode effects.
Histogram.ipynb	Understanding distributions using histograms and bins.
Scatter_Plots.ipynb	Plotting relationships between variables with scatter plots.
barchart.jpg / line graph.png / sample_histogram.png / scatter-plot.png / pie-chart.svg / histogram.svg	Sample visual outputs from the notebooks.

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🔹 Advanced

Notebook	Description
Advanced_Scatter_Plots.ipynb	Enhanced scatter plots using size, color maps, and annotations.
Subplots.ipynb	Creating multi-plot grids and complex layouts.
3d_graphs_plotting.ipynb	Rendering 3D plots using Matplotlib’s mplot3d toolkit.
heatmap.ipynb	Heatmaps for correlation, matrix visualization, and color maps.
Pandas_plot.ipynb	Using Pandas' built-in .plot() for quick data visualizations.

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🔹 Datasets

Dataset	Description
IPL_Ball_by_Ball_2008_2022.csv	Ball-by-ball IPL data (2008–2022).
batsman_season_record.csv	Season-wise batting stats.
batter.csv	Player-wise batting details.
gayle-175.csv	Chris Gayle’s historic 175* innings data.
sharma-kohli.csv	Sharma vs. Kohli performance comparison.
vk.csv	Virat Kohli’s performance dataset.
iris.csv	Classic Iris dataset for ML visualizations.
big-array.npy	Large NumPy array for performance & plotting tests.

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📚 Learning Resources

• 🔹 CampusX - Basic Matplotlib
• 🔹 CampusX - Advance Matplotlib

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🧰 Tools & Environment

• Python 3.x
• Matplotlib
• NumPy
• Jupyter Notebook

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✨ Author

Shafaq Aslam
📍 Passionate learner exploring Data Visualization, Data Science, and AI through hands-on projects.

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🔖 Tags for SEO

matplotlib python data-visualization charts plots scatter-plot line-plot bar-chart histogram jupyter-notebook visual-storytelling data-analysis learning-lab

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“Visualize your data, uncover its story, and let your plots speak louder than words.”