Python Practice Notebooks – NumPy & Matplotlib

This repository contains Jupyter Notebooks that provide practical exercises for learning the fundamentals of NumPy and Matplotlib.

📘 Overview

🟦 NumPy Practice (numpy_practice_class1.ipynb)

• Covers the basics of NumPy, including:
• Creating NumPy arrays
• Indexing and slicing arrays
• Array operations (mathematical & logical)
• Reshaping arrays
• Stacking arrays (horizontal & vertical stacking)
• Basic manipulations and computations

📂 File Details:

• numpy_practice_class1.ipynb → 89 cells (86 code, 2 markdown).

🟥 Matplotlib Practice (Matplotlib_MWF.ipynb)

• Focuses on data visualization using Matplotlib, including:
• Plotting points and lines
• Customizing titles, labels, and legends
• Different types of plots (line, bar, scatter, histogram, pie, etc.)
• Styling with colors, markers, and line types
• Creating multiple plots and subplots

📂 File Details:

• Matplotlib_MWF.ipynb → 59 cells (49 code, 10 markdown).

🚀 Getting Started

• Clone this repository or download the notebooks.
• Open them in Jupyter Notebook, JupyterLab, or Google Colab.
• Run the cells sequentially to explore and practice.

🔎 Example Code

NumPy Example:

import numpy as np
a = np.array([1, 2, 3])   # forward indexing starts from 0
print(a)

Matplotlib Example:

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]

plt.plot(x, y, marker='o')
plt.title("Simple Line Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

🎓 Learning Source

• These practice notebooks were created as part of my NASSCOM class, focusing on strengthening foundations in Python, NumPy, and Matplotlib.