Axis Labels and Titles

Always label your charts

Without labels, your chart is incomplete. McKinney’s rule of thumb: set_xlabel names the x-axis, set_title names the whole subplot, and both can be set together with one call to ax.set(title=..., xlabel=..., ylabel=...) — handy once you’re labelling many subplots at once.

diagram Labelling a plot mermaid

  flowchart LR
  A["Raw plot"] --> B["ax.set_xlabel('Day')"]
  B --> C["ax.set_ylabel('Orders')"]
  C --> D["ax.set_title('what changed, not just the chart type')"]
  D --> E["Reader understands the chart without extra context"]

Every plot needs a title (the question it answers) plus labelled, unit-carrying axes.

Labels

import matplotlib.pyplot as plt
 
x = [1, 2, 3, 4]
y = [100, 120, 90, 150]
 
plt.figure(figsize=(7, 4))
plt.plot(x, y, marker="o")
plt.title("Daily orders")
plt.xlabel("Day")
plt.ylabel("Orders")
plt.tight_layout()
plt.show()

Include units

Examples:

• Revenue (₹)
• Duration (seconds)
• Conversion rate (%)

Tip

A good title explains the question, not just the chart type.

Bad: “Line chart”

Better: “Daily orders increased after campaign launch”

From the book

McKinney shows that set_xticks and set_xticklabels are two separate steps: the first says where to put ticks along the data range, the second says what text to show there (optionally rotated with rotation=30). If you only rename the labels without first fixing the tick positions, the labels can end up next to the wrong ticks.

Next

Continue to Legends and Colors to distinguish multiple series clearly.

🧪 Try It Yourself

Exercise 1 – Title and axis labels together

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Exercise 2 – Custom tick labels

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Exercise 3 – Rotate long labels

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