How to set a Matplotlib style theme

Style sheets in Matplotlib collect visual defaults such as grid behavior, line widths, marker sizes, legend frames, and background colors. A theme keeps charts from the same report or project visually consistent without repeating the same styling arguments on every plot call.

plt.style.use() applies a built-in style name, a path to a .mplstyle file, or a list of styles. When a list is used, Matplotlib applies entries from left to right, so a project style file can refine a built-in theme such as ggplot.

Style sheets are best for appearance defaults that should apply across a figure or script. Direct plot arguments still belong on individual series when one line, marker, or bar needs a fixed color or label, and non-style runtime settings such as the backend should stay outside .mplstyle files.

1. Confirm the built-in style names available in the active Python environment.

   $ python - <<'PY'
   import matplotlib.pyplot as plt
   print("ggplot available:", "ggplot" in plt.style.available)
   print("seaborn-v0_8 available:", "seaborn-v0_8" in plt.style.available)
   PY
   ggplot available: True
   seaborn-v0_8 available: True

   plt.style.available lists built-in styles and styles installed in the user style library. Current Matplotlib uses versioned Seaborn style names such as seaborn-v0_8.

2. Save a project style sheet as report-theme.mplstyle.

   axes.facecolor: white
   axes.edgecolor: 0.35
   axes.grid: True
   axes.titleweight: bold
   grid.color: 0.85
   grid.linestyle: --
   lines.linewidth: 2.8
   lines.markersize: 7
   legend.frameon: True
   legend.facecolor: white
   figure.facecolor: white

   Use a .mplstyle file for visual defaults that should travel with a project. Settings such as backend are ignored in style sheets because they are runtime configuration, not plot appearance.

3. Save the themed plot script as style_theme_set.py.

   style_theme_set.py

   from pathlib import Path
    
   import matplotlib
   import matplotlib.pyplot as plt
    
   plt.style.use(["ggplot", "report-theme.mplstyle"])
    
   months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
   website = [38, 45, 49, 54, 58, 63]
   mobile = [22, 27, 31, 33, 40, 44]
    
   fig, ax = plt.subplots(layout="constrained")
   ax.plot(months, website, marker="o", label="Website")
   ax.plot(months, mobile, marker="s", label="Mobile")
   ax.set_title("Monthly signups by channel")
   ax.set_xlabel("Month")
   ax.set_ylabel("Signups")
   ax.legend()
    
   output = Path("style-theme-set.png")
   fig.savefig(output, dpi=160)
   plt.close(fig)
    
   print(f"matplotlib {matplotlib.__version__} ({matplotlib.get_backend()} backend)")
   print("styles applied: ggplot + report-theme.mplstyle")
   print(f"axes facecolor: {plt.rcParams['axes.facecolor']}")
   print(f"grid enabled: {plt.rcParams['axes.grid']}")
   print(f"line width: {plt.rcParams['lines.linewidth']}")
   print(f"saved: {output}")
   print(f"bytes: {output.stat().st_size}")

   The built-in ggplot style sets the base look, and report-theme.mplstyle overrides selected defaults for the project. Use plt.style.use(“ggplot”) when no local style file is needed.

4. Run the script and confirm the active style settings.

   $ python style_theme_set.py
   matplotlib 3.11.0 (Agg backend)
   styles applied: ggplot + report-theme.mplstyle
   axes facecolor: white
   grid enabled: True
   line width: 2.8
   saved: style-theme-set.png
   bytes: 64409

   

   The byte count can change with Matplotlib, fonts, backend, or DPI differences. The style settings and saved filename confirm that the theme loaded and the figure was written.

5. Inspect the saved PNG dimensions when the script runs without an interactive display.

   $ python - <<'PY'
   from PIL import Image
   image = Image.open("style-theme-set.png")
   print(image.size)
   PY
   (1024, 768)

   The dimensions come from the default figure size and the 160 DPI value passed to fig.savefig().

6. Remove the temporary files when they were created only for testing.

   $ rm report-theme.mplstyle style_theme_set.py style-theme-set.png

   Keep report-theme.mplstyle in the project when the theme should be reused by other plotting scripts.