Highlight and annotate pattern in Matplotlib - Step-by-Step Execution

Concept Flow - Highlight and annotate pattern

Create plot with data

↓

Identify pattern region

↓

Add highlight (e.g., shaded area)

↓

Add annotation text and arrow

↓

Display final plot

This flow shows how to create a plot, highlight a specific pattern area, add annotation, and then display the plot.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
x = range(10)
y = [1,2,3,7,8,7,3,2,1,0]
plt.plot(x, y)
plt.axvspan(3, 5, color='yellow', alpha=0.3)
plt.annotate('Peak pattern', xy=(4,8), xytext=(6,9), arrowprops=dict(facecolor='black'))
plt.show()

This code plots data, highlights the peak region between x=3 and x=5 with a yellow shade, and adds an annotation pointing to the peak.

Execution Table

Step	Action	Effect on Plot	Annotation Added
1	Plot line with x and y data	Line graph appears showing values rising and falling	No
2	Highlight region between x=3 and x=5	Yellow shaded area appears over peak region	No
3	Add annotation text 'Peak pattern' at (6,9) pointing to (4,8)	Arrow and text label appear pointing to peak	Yes
4	Display plot	Final plot with line, highlight, and annotation shown	Yes

💡 Plot displayed with highlighted pattern and annotation

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
x	range(10)	range(10)	range(10)	range(10)	range(10)
y	[1,2,3,7,8,7,3,2,1,0]	[1,2,3,7,8,7,3,2,1,0]	[1,2,3,7,8,7,3,2,1,0]	[1,2,3,7,8,7,3,2,1,0]	[1,2,3,7,8,7,3,2,1,0]
highlight_region	None	None	x=3 to 5 shaded yellow	x=3 to 5 shaded yellow	x=3 to 5 shaded yellow
annotation	None	None	None	Text 'Peak pattern' with arrow at (6,9)->(4,8)	Text 'Peak pattern' with arrow at (6,9)->(4,8)

Key Moments - 2 Insights

Why does the highlight only cover the x range 3 to 5 and not the whole plot?

Because plt.axvspan(3, 5, ...) specifically shades the vertical span between x=3 and x=5, as shown in execution_table step 2.

How does the annotation arrow know where to point?

The annotation uses xy=(4,8) as the point to highlight and xytext=(6,9) as the text location, creating an arrow between them (execution_table step 3).

Visual Quiz - 3 Questions

Look at the execution table, at which step is the yellow highlight added?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Check the 'Action' column for when 'Highlight region' is added.

According to variable_tracker, what is the value of 'annotation' after step 2?

A None

B Text 'Peak pattern' with arrow

C x=3 to 5 shaded yellow

D Range of x values

💡 Hint

Look at the 'annotation' row under 'After Step 2' column.

If we change the highlight range to x=2 to 6, what changes in the execution_table?

A Line plot changes

B Annotation text changes

C Step 2 highlight region changes to x=2 to 6 shaded yellow

D No changes

💡 Hint

Focus on the 'Effect on Plot' column in step 2.

Concept Snapshot

Highlight and annotate pattern in matplotlib:
- Use plt.plot() to draw data
- Use plt.axvspan(start, end, color, alpha) to highlight x-range
- Use plt.annotate(text, xy, xytext, arrowprops) to add notes
- Display with plt.show()
Key: Highlight focuses attention; annotation explains it.

Full Transcript

This visual execution shows how to highlight and annotate a pattern in a matplotlib plot. First, data is plotted as a line graph. Then, a vertical shaded area highlights the pattern region between x=3 and x=5. Next, an annotation with text 'Peak pattern' and an arrow points to the peak at (4,8). Finally, the plot is displayed with all these elements visible. Variables like x and y remain unchanged, while highlight_region and annotation are added step-by-step. Common confusions include why the highlight covers only part of the plot and how the annotation arrow points correctly. The quizzes test understanding of when highlights and annotations appear and how changes affect the plot.