Projects for Numpy + Matplotlib: Beginner to Advanced

1. Weather Data Analysis

• Description: Generate or load weather data (temperature, humidity) for a month or year.
• NumPy tasks: Compute daily averages, moving averages, anomalies, correlations.
• Matplotlib tasks: Line plots for trends, bar charts for daily highs/lows, heatmaps for temperature variations.
• Bonus: Animate temperature changes over a week or month.

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2. Stock Market Simulator

• Description: Simulate a stock’s price over time using random walks.
• NumPy tasks: Generate random returns, calculate cumulative returns, compute moving averages, volatility.
• Matplotlib tasks: Plot stock price over time, overlay moving averages, create subplots for volatility, or candlestick-style charts.
• Bonus: Compare multiple stocks on the same chart.

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3. Image Manipulation and Visualization

• Description: Load an image as a NumPy array and manipulate it.
• NumPy tasks: Convert to grayscale, apply filters, rotate/flip, compute histograms.
• Matplotlib tasks: Display original vs. modified images side by side, show color histograms.
• Bonus: Implement edge detection or simple thresholding.

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4. 2D Random Walk Simulation

• Description: Simulate particles moving randomly on a plane.
• NumPy tasks: Generate x, y positions over time, compute distances traveled.
• Matplotlib tasks: Plot trajectories, scatter plots showing particle positions, animate the motion.
• Bonus: Add obstacles or boundaries and study effects.

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5. Fourier Series Visualization

• Description: Visualize how Fourier series approximate periodic functions.
• NumPy tasks: Compute Fourier coefficients, sum series terms.
• Matplotlib tasks: Animate the approximation of a square or triangle wave as more terms are added.
• Bonus: Show frequency spectrum as a bar plot.

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6. Population Growth and Logistic Models

• Description: Simulate population growth using exponential and logistic models.
• NumPy tasks: Compute population over time with different growth rates, carrying capacities.
• Matplotlib tasks: Plot growth curves, compare exponential vs. logistic growth, add multiple curves in one plot.
• Bonus: Animate population change over time.

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7. Mandelbrot or Julia Set Visualization

• Description: Generate fractals using complex numbers.
• NumPy tasks: Iterate complex equations, detect divergence, generate array for plotting.
• Matplotlib tasks: Use imshow to visualize the set with a colormap.
• Bonus: Allow interactive zooming or color changes.

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8. Heatmap of a Mathematical Function

• Description: Visualize functions like sin(x)*cos(y) or exp(-x^2 - y^2) over a grid.
• NumPy tasks: Create a meshgrid and evaluate the function.
• Matplotlib tasks: Use imshow or contourf to create heatmaps.
• Bonus: Animate how the function changes with a parameter.

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9. Dice Rolling Simulation

• Description: Simulate rolling multiple dice and analyzing outcomes.
• NumPy tasks: Generate random dice rolls, compute probabilities, averages, histograms.
• Matplotlib tasks: Bar charts for outcomes, line plots for running averages, pie charts for probabilities.
• Bonus: Simulate biased dice or multiple players.

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10. 3D Surface Plots

• Description: Explore 3D functions like z = sin(sqrt(x^2 + y^2)).
• NumPy tasks: Generate meshgrid and compute z-values.
• Matplotlib tasks: Use plot_surface or contour3D to visualize.
• Bonus: Animate rotation of the 3D plot or vary parameters.

Roadmap

1. Dice Rolling Simulation (Beginner)

• Goal: Simulate rolling dice and visualize probabilities.
• NumPy skills: Random number generation, array manipulation, probability calculations.
• Matplotlib skills: Bar plots, histograms, pie charts.
• Extra challenge: Simulate multiple players and compare outcomes.

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2. 2D Random Walk (Beginner → Intermediate)

• Goal: Simulate multiple particles moving randomly in 2D.
• NumPy skills: Array broadcasting, cumulative sum, distance calculations.
• Matplotlib skills: Line plots for trajectories, scatter plots, optional animation.
• Extra challenge: Add obstacles or boundaries.

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3. Stock Market Simulator (Intermediate)

• Goal: Simulate stock prices using random walks and visualize trends.
• NumPy skills: Random sampling, cumulative products, moving averages, volatility calculation.
• Matplotlib skills: Line plots, subplots, multiple series comparison.
• Extra challenge: Simulate multiple stocks or a portfolio and visualize correlations.

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4. Heatmap of Mathematical Functions (Intermediate)

• Goal: Visualize 2D functions like sin(sqrt(x^2 + y^2)).
• NumPy skills: Meshgrid creation, function evaluation over grids.
• Matplotlib skills: imshow, contourf, colorbars.
• Extra challenge: Animate function changes over time or with parameters.

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5. Image Processing & Visualization (Intermediate → Advanced)

• Goal: Manipulate images using NumPy arrays.
• NumPy skills: Array slicing, manipulation, filtering, histogram calculation.
• Matplotlib skills: Display images, histograms, side-by-side comparisons.
• Extra challenge: Implement edge detection, convolution filters, or color transformations.

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6. Mandelbrot / Julia Set Visualization (Advanced)

• Goal: Generate fractals using complex numbers and visualize them.
• NumPy skills: Complex array computations, divergence checking, vectorization for speed.
• Matplotlib skills: imshow with colormaps, zooming.
• Extra challenge: Interactive zooming, coloring by iteration counts, or animate parameter changes.

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