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Matplotlib Visualization

Topic: Visualization

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Matplotlib Basics

Matplotlib is Python's primary plotting library. It provides fine-grained control over visualizations.

Basic Plots

Line plots: plt.plot(x, y). Scatter plots: plt.scatter(x, y). Bar charts: plt.bar(x, height). Histograms: plt.hist(data).

Figure and axes control the structure: fig, ax = plt.subplots(). Multiple plots on one figure.

Customization: labels, titles, legends, colors, line styles. The object-oriented interface gives precise control.

Subplots and Layouts

Subplots create multiple plots: fig, axes = plt.subplots(2, 2). Each axes object controls its plot.

GridSpec provides more complex layouts. constrained_layout and tight_layout handle spacing.

Saving and Show

Plots display with plt.show(). Saving: fig.savefig('plot.png', dpi=300). Formats: png, pdf, svg.

Key Takeaways

  1. Matplotlib provides comprehensive plotting capabilities
  2. Object-oriented interface offers fine control
  3. Subplots and layouts enable complex visualizations

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