AME 209: 17. Plotting with Matplotlib

By the end of this section, students should be able to... • Generate basic line plots using matplotlib.pyplot • Label plots with axes, titles, and legends • Customize plots (colors, styles, markers) • Create multiple plots (subplots or overlayed) • Save plots to image files • Understand the difference between MATLAB-style and object-oriented usage

Matplotlib

A Python library used to create static, animated, and interactive visualizations.

pyplot

A submodule of matplotlib that mimics MATLAB-style plotting commands.
import matplotlib.pyplot as plt -- Standard import convention to access plotting functions with a shorter alias.

Basic Plot

A visual representation of x vs. y data using plt.plot(x, y).

Axes Labeling

Adding context to plots using xlabel(), ylabel(), and title() functions.

Gridlines

Optional lines on the plot background for reference, toggled using plt.grid(True) or False.

Legend

A descriptive label for each plotted line; shown using plt.legend() if label= was provided in the plot call.

Plot Display

The command plt.show() renders the plot in a window or output cell.

Customization

Control visual style with arguments like color, linestyle, marker, and linewidth.Li

Line Styles

Define how lines appear: solid (-), dashed (--), dotted (:), or dash-dot (-.').

Markers

Symbols at each data point (e.g., o for circles, ^ for triangles, s for squares).

Colors

Use single-letter codes ('r' for red) or hex codes ('#1f77b4') for precise color control.

Axis Limits

Set viewing ranges using plt.axis([xmin, xmax, ymin, ymax]) or separately with xlim()/ylim().

Overlayed Plots

Calling plt.plot() multiple times adds several lines to the same graph—useful for comparisons.

Subplots

Organize multiple plots in a grid using plt.subplot(n_rows, n_cols, plot_index).

tight_layout()

Automatically adjusts spacing to prevent overlapping labels or axes in subplot grids.

MATLAB vs. Python Plotting

Python allows both MATLAB-style procedural plots and object-oriented plotting for complex needs.

Plot Use (in Engineering)

Useful for visualizing functions, simulations, and comparative data analysis.