Zoom and pan with toolbar in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What happens when you click the zoom button in matplotlib toolbar?

Consider a matplotlib plot with the default toolbar enabled. What is the immediate effect of clicking the zoom button?

Matplotlib

import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [10, 20, 25, 30])
plt.show()

A The plot area becomes interactive allowing you to draw a rectangle to zoom into a specific region.

B The plot automatically zooms into the center of the graph by a fixed factor.

C The plot resets to the original view without any zoom applied.

D The plot switches to pan mode, allowing you to drag the plot around.

💡 Hint

Think about what zooming usually means in a graph interface.

Clicking the zoom button activates a mode where you can select a rectangular area on the plot to zoom into that specific region.

❓ data_output

intermediate

What are the axis limits after panning right by 2 units?

Given a plot with x-axis limits from 0 to 10, if you pan the plot right by 2 units using the toolbar, what will be the new x-axis limits?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.set_xlim(0, 10)
ax.set_ylim(0, 5)
# Assume user pans right by 2 units
new_xlim = (2, 12)
print(new_xlim)

A (2, 12)

B (-2, 8)

C (0, 10)

D (10, 20)

💡 Hint

Panning right shifts the view window to higher x values.

Panning right by 2 units moves both limits 2 units higher, so from (0,10) to (2,12).

❓ visualization

advanced

Identify the effect of zooming on y-axis limits

Look at the two plots below. The first plot shows the original y-axis limits from 0 to 100. The second plot is after zooming into the y-range 20 to 40. What is the new y-axis limit range?

Matplotlib

import matplotlib.pyplot as plt
fig, axs = plt.subplots(1, 2, figsize=(8, 4))
axs[0].plot(range(101), range(101))
axs[0].set_ylim(0, 100)
axs[0].set_title('Original')
axs[1].plot(range(101), range(101))
axs[1].set_ylim(20, 40)
axs[1].set_title('Zoomed')
plt.show()

A The y-axis limits remain (0, 100), no zoom applied.

B The y-axis limits are (20, 40), showing a zoomed-in vertical range.

C The y-axis limits are inverted (40, 20), causing an error.

D The y-axis limits are automatically adjusted to (10, 50).

💡 Hint

Zooming changes the visible range to a smaller subset.

Zooming into y-range 20 to 40 sets the y-axis limits exactly to (20, 40), focusing on that part of the data.

🔧 Debug

advanced

Why does this pan code not update the plot view?

Consider this code snippet to pan a matplotlib plot by changing x-axis limits. Why does the plot not update after running this?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1,2,3,4], [10,20,25,30])
ax.set_xlim(0, 10)
ax.set_xlim(ax.get_xlim()[0] + 2, ax.get_xlim()[1] + 2)
# Missing plt.show() or canvas draw update

A Because the plot data must be cleared before changing limits.

B Because set_xlim does not change the axis limits.

C Because plt.show() or fig.canvas.draw() is missing to refresh the plot display.

D Because the pan operation requires changing y-axis limits, not x-axis.

💡 Hint

Think about what is needed to update a plot after changing properties programmatically.

Changing axis limits alone does not refresh the plot display. You must call plt.show() again or use fig.canvas.draw() to update the view.

🚀 Application

expert

How to programmatically zoom into a specific rectangle area in matplotlib?

You want to programmatically zoom into the rectangle defined by x from 2 to 5 and y from 10 to 20 on an existing matplotlib plot. Which code snippet correctly achieves this?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(range(10), [i*3 for i in range(10)])

A

ax.zoom(2, 5, 10, 20)
plt.show()

B

plt.xlim(2, 5)
plt.ylim(10, 20)
plt.show()

C

ax.pan(2, 5)
ax.pan(10, 20)
plt.draw()

D

ax.set_xlim(2, 5)
ax.set_ylim(10, 20)
plt.draw()

💡 Hint

Zooming programmatically means setting axis limits to the desired rectangle.

Setting x and y axis limits to the rectangle coordinates zooms into that area. plt.draw() refreshes the plot.