GridSpec for complex layouts in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this GridSpec subplot arrangement?

Consider the following code using matplotlib.gridspec.GridSpec. What will be the number of subplots created and their arrangement?

Matplotlib

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

fig = plt.figure()
gs = GridSpec(3, 3, figure=fig)
ax1 = fig.add_subplot(gs[0, :])
ax2 = fig.add_subplot(gs[1, :-1])
ax3 = fig.add_subplot(gs[1:, -1])
ax4 = fig.add_subplot(gs[-1, 0])
plt.close(fig)
print(len(fig.axes))

A 5

B 4

C 3

D 6

💡 Hint

Count each add_subplot call and check if any overlap or replacement occurs.

The code creates 4 subplots using different GridSpec slices. Each add_subplot adds a new axis, so total is 4.

❓ data_output

intermediate

What is the shape of the GridSpec layout?

Given this GridSpec code, what is the shape of the grid and which cells does gs[1:3, 0:2] cover?

Matplotlib

from matplotlib.gridspec import GridSpec

gs = GridSpec(4, 4)
covered_cells = [(r, c) for r in range(1, 3) for c in range(0, 2)]
print((gs.nrows, gs.ncols), covered_cells)

A (4, 4) and cells [(1, 0), (1, 1), (2, 0), (2, 1)]

B (3, 3) and cells [(1, 0), (1, 1), (2, 0), (2, 1)]

C (4, 4) and cells [(0, 1), (0, 2), (1, 1), (1, 2)]

D (3, 3) and cells [(0, 1), (0, 2), (1, 1), (1, 2)]

💡 Hint

GridSpec(4,4) creates a 4x4 grid. The slice selects rows 1 and 2, columns 0 and 1.

The GridSpec is 4 rows by 4 columns. The slice 1:3 means rows 1 and 2, and 0:2 means columns 0 and 1, so the covered cells are those four coordinates.

❓ visualization

advanced

Identify the correct GridSpec layout visualization

Which option shows the correct layout of subplots created by this code?

Matplotlib

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

fig = plt.figure(figsize=(6, 4))
gs = GridSpec(2, 3, figure=fig)
ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[0, 1:])
ax3 = fig.add_subplot(gs[1, :2])
ax4 = fig.add_subplot(gs[1, 2])
plt.close(fig)
# The question is about the layout shape, not the plot content.

A One small subplot on top left, one spanning top right two columns, one spanning bottom left two columns, one small bottom right

B Four equally sized subplots in a 2x2 grid

C Three subplots stacked vertically

D Two subplots side by side on top, two stacked vertically on bottom left

💡 Hint

Look at the slices: gs[0, 0], gs[0, 1:], gs[1, :2], gs[1, 2].

The first subplot is top-left cell. The second spans top row columns 1 and 2. The third spans bottom row columns 0 and 1. The last is bottom row column 2 alone.

🔧 Debug

advanced

What error does this GridSpec code raise?

What error will this code raise when executed?

Matplotlib

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

fig = plt.figure()
gs = GridSpec(2, 2, figure=fig)
ax1 = fig.add_subplot(gs[2, 0])
plt.close(fig)

A TypeError: 'GridSpec' object is not subscriptable

B ValueError: Invalid subplot specification

C IndexError: index 2 is out of bounds for axis 0 with size 2

D No error, subplot created successfully

💡 Hint

Check the grid size and the index used in gs[2, 0].

The GridSpec has 2 rows (indices 0 and 1). Index 2 is out of range, so an IndexError is raised.

🚀 Application

expert

How to create a complex layout with nested GridSpec?

You want to create a figure with two main columns. The left column has two rows of equal height. The right column is a single subplot spanning full height. Which code snippet correctly creates this layout using nested GridSpec?

A

fig = plt.figure()
gs = GridSpec(2, 2, figure=fig)
ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[1, 0])
ax3 = fig.add_subplot(gs[:, 1])

B

fig = plt.figure()
gs = GridSpec(2, 1, figure=fig)
gs_left = GridSpec(1, 2, subplot_spec=gs[0, 0])
ax1 = fig.add_subplot(gs_left[0, 0])
ax2 = fig.add_subplot(gs_left[0, 1])
ax3 = fig.add_subplot(gs[1, 0])

C

fig = plt.figure()
gs = GridSpec(1, 2, figure=fig)
gs_left = GridSpec(1, 2, subplot_spec=gs[0, 0])
ax1 = fig.add_subplot(gs_left[0, 0])
ax2 = fig.add_subplot(gs_left[0, 1])
ax3 = fig.add_subplot(gs[0, 1])

D

fig = plt.figure()
gs = GridSpec(1, 2, figure=fig)
gs_left = GridSpec(2, 1, subplot_spec=gs[0, 0])
ax1 = fig.add_subplot(gs_left[0, 0])
ax2 = fig.add_subplot(gs_left[1, 0])
ax3 = fig.add_subplot(gs[0, 1])

💡 Hint

Think about how to split the figure into two columns, then split the left column into two rows.

Option D uses a nested GridSpec: outer GridSpec(1, 2) splits into two columns. The left column (gs[0, 0]) is subdivided with nested GridSpec(2, 1) into two equal-height rows. The right column (gs[0, 1]) is a single subplot spanning the full height.

Practice

1. What is the main purpose of using GridSpec in matplotlib?

easy

A. To divide a figure into a flexible grid for placing subplots.

B. To change the color of the plot background.

C. To add titles to individual subplots automatically.

D. To save the figure in different file formats.

Solution

1. Step 1: Understand GridSpec's role

   GridSpec is designed to split a figure into rows and columns for subplot placement.

2. Step 2: Compare options

   Only To divide a figure into a flexible grid for placing subplots. describes this grid division purpose; others describe unrelated features.

3. Final Answer:

   To divide a figure into a flexible grid for placing subplots. -> Option A

4. Quick Check:

   GridSpec = flexible grid layout [OK]

Hint: GridSpec = grid layout for subplots [OK]

Common Mistakes:

• Confusing GridSpec with styling or saving functions
• Thinking GridSpec adds titles automatically
• Assuming GridSpec changes colors

2. Which of the following is the correct way to create a 2x3 GridSpec object named gs?

easy

A. gs = GridSpec(3, 2)

B. gs = GridSpec(2, 3)

C. gs = GridSpec(rows=3, cols=2)

D. gs = GridSpec(2)

Solution

1. Step 1: Recall GridSpec syntax

   GridSpec takes number of rows first, then columns: GridSpec(nrows, ncols).

2. Step 2: Match 2 rows and 3 columns

   gs = GridSpec(2, 3) uses GridSpec(2, 3), which is correct for 2 rows and 3 columns.

3. Final Answer:

   gs = GridSpec(2, 3) -> Option B

4. Quick Check:

   GridSpec(rows, cols) = (2, 3) [OK]

Hint: Rows first, columns second in GridSpec() [OK]

Common Mistakes:

• Swapping rows and columns order
• Using keyword arguments incorrectly
• Passing only one number instead of two

3. What will be the shape of the subplot created by fig.add_subplot(gs[0:2, 1]) if gs = GridSpec(3, 3)?

medium

A. A subplot spanning rows 0 and 1 in column 1 (tall and narrow).

B. A subplot in row 0, column 1 only (small square).

C. A subplot spanning all rows in column 1 (very tall).

D. A subplot spanning rows 1 and 2 in column 1.

Solution

1. Step 1: Understand slicing in GridSpec

   gs[0:2, 1] selects rows 0 and 1 (two rows) in column 1.

2. Step 2: Determine subplot shape

   It creates a subplot spanning two rows vertically and one column horizontally, so tall and narrow.

3. Final Answer:

   A subplot spanning rows 0 and 1 in column 1 (tall and narrow). -> Option A

4. Quick Check:

   gs[0:2,1] = rows 0-1, col 1 [OK]

Hint: Slice rows then columns in GridSpec to get subplot size [OK]

Common Mistakes:

• Confusing row and column indices
• Assuming slice includes row 2
• Thinking it spans all rows

4. Identify the error in this code snippet using GridSpec:

fig = plt.figure()
gs = GridSpec(2, 2)
ax = fig.add_subplot(gs[2, 1])

medium

A. TypeError because gs is not callable.

B. SyntaxError due to missing parentheses in GridSpec.

C. IndexError because row index 2 is out of range for 2 rows.

D. No error; code runs fine.

Solution

1. Step 1: Check GridSpec size

   GridSpec(2, 2) creates 2 rows indexed 0 and 1 only.

2. Step 2: Check subplot indexing

   gs[2, 1] tries to access row 2, which does not exist, causing IndexError.

3. Final Answer:

   IndexError because row index 2 is out of range for 2 rows. -> Option C

4. Quick Check:

   Index out of range = IndexError [OK]

Hint: Check GridSpec row/column indices start at 0 [OK]

Common Mistakes:

• Assuming indices start at 1
• Confusing syntax errors with index errors
• Ignoring zero-based indexing

5. You want to create a figure with 3 subplots: one large plot on the left spanning all rows, and two smaller plots stacked vertically on the right. Which GridSpec slicing correctly achieves this layout for gs = GridSpec(2, 2)?

hard

A. Left plot: gs[0, :], Right top: gs[1, 0], Right bottom: gs[1, 1]

B. Left plot: gs[:, 1], Right top: gs[0, 0], Right bottom: gs[1, 0]

C. Left plot: gs[0, 0], Right top: gs[0, 1], Right bottom: gs[1, 1]

D. Left plot: gs[:, 0], Right top: gs[0, 1], Right bottom: gs[1, 1]

Solution

1. Step 1: Understand layout goal

   Left plot spans all rows in first column; right side has two stacked plots in second column.

2. Step 2: Match slicing to layout

   gs[:, 0] selects all rows in column 0 (left plot). gs[0, 1] and gs[1, 1] select top and bottom right plots.

3. Final Answer:

   Left plot: gs[:, 0], Right top: gs[0, 1], Right bottom: gs[1, 1] -> Option D

4. Quick Check:

   Use colon for full rows, index for columns [OK]

Hint: Use colon to span all rows or columns in GridSpec [OK]

Common Mistakes:

• Mixing row and column indices
• Using single indices instead of slices for spanning
• Swapping left and right columns