How to create a bar chart in Matplotlib

Bar charts compare categorical values by drawing one rectangle for each category. In Matplotlib, they fit counts, totals, rankings, and other side-by-side measurements where the category label matters as much as the numeric value.

The object-oriented interface keeps the Figure and Axes explicit. plt.subplots() creates the drawing area, ax.bar() draws the rectangles, ax.bar_label() writes value labels on the bars, and fig.savefig() exports the finished chart.

Categorical labels can be passed directly to ax.bar() when each label is unique. Saving a PNG and printing the stored title, axis labels, bar count, filename, and byte size checks the chart without relying on an interactive window.

1. Save the bar chart script as create_bar_chart.py.

   create_bar_chart.py

   from pathlib import Path
    
   import matplotlib.pyplot as plt
    
   plans = ["Standard", "Pro", "Enterprise", "Education"]
   signups = [180, 245, 90, 135]
   colors = ["tab:blue", "tab:orange", "tab:green", "tab:red"]
    
   fig, ax = plt.subplots(layout="constrained")
   bars = ax.bar(plans, signups, color=colors)
   ax.bar_label(bars, padding=3)
   ax.set_title("Quarterly signups by plan")
   ax.set_xlabel("Plan")
   ax.set_ylabel("Signups")
   ax.set_ylim(0, max(signups) + 60)
    
   output = Path("plan-signups-bar-chart.png")
   fig.savefig(output, dpi=160)
   plt.close(fig)
    
   print(f"bars: {len(bars)}")
   print(f"title: {ax.get_title()}")
   print(f"x label: {ax.get_xlabel()}")
   print(f"y label: {ax.get_ylabel()}")
   print(f"saved: {output}")
   print(f"bytes: {output.stat().st_size}")

   ax.bar() accepts the plan names as categorical x values, and ax.bar_label() places each count above its bar.

2. Run the script from the Python environment that has Matplotlib installed.

   $ python create_bar_chart.py
   bars: 4
   title: Quarterly signups by plan
   x label: Plan
   y label: Signups
   saved: plan-signups-bar-chart.png
   bytes: 33385

   The byte count can change with Matplotlib, font, backend, or DPI differences. A nonzero byte count and the expected filename confirm that the PNG was written.

3. Open plan-signups-bar-chart.png and confirm the plotted result.

   The image should show four colored bars labeled Standard, Pro, Enterprise, and Education, with the highest bar for Pro.

4. Replace the plan labels, values, and colors with the categories for the real dataset.

   plans = ["North", "South", "East", "West"]
   signups = [120, 98, 143, 111]
   colors = ["tab:blue", "tab:blue", "tab:blue", "tab:blue"]

   Keep the category and value sequences the same length because each label needs one numeric bar height.

5. Remove the practice files when the chart was only a test.

   $ rm create_bar_chart.py plan-signups-bar-chart.png