GridSpec for complex layouts in Matplotlib - Mini Project: Build & Apply

GridSpec for complex layouts

📖 Scenario: You are creating a report with multiple charts arranged in a complex layout. Using matplotlib's GridSpec, you will place different plots in specific grid positions to make the report clear and organized.

🎯 Goal: Build a figure with a 3x3 grid layout using GridSpec. Place three plots: a line plot spanning the top row, a scatter plot in the bottom-left cell, and a bar plot spanning the bottom-right two cells.

📋 What You'll Learn

Create a 3x3 GridSpec layout

Place a line plot spanning the entire top row

Place a scatter plot in the bottom-left cell

Place a bar plot spanning the bottom-right two cells

Use plt.show() to display the figure

💡 Why This Matters

🌍 Real World

Data scientists often need to create reports with multiple charts arranged neatly to compare data visually.

💼 Career

Knowing how to use GridSpec helps you build professional and clear visualizations for presentations and dashboards.

1

Create a 3x3 GridSpec layout

Import matplotlib.pyplot as plt and GridSpec from matplotlib.gridspec. Then create a figure called fig with size (8, 6) and a GridSpec object called gs with 3 rows and 3 columns.

Matplotlib

# Your code here

Need a hint?

Use plt.figure(figsize=(8, 6)) to create the figure and GridSpec(3, 3, figure=fig) to create the grid layout.

2

Add a line plot spanning the top row

Create an axes called ax1 using fig.add_subplot(gs[0, :]) to span the entire top row. Plot a line with x values [0, 1, 2, 3] and y values [10, 20, 25, 30] on ax1.

Matplotlib

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

fig = plt.figure(figsize=(8, 6))
gs = GridSpec(3, 3, figure=fig)
# Your code here

Need a hint?

Use gs[0, :] to select the entire first row for the line plot.

3

Add a scatter plot in the bottom-left cell

Create an axes called ax2 using fig.add_subplot(gs[2, 0]) for the bottom-left cell. Plot a scatter plot with x values [1, 2, 3] and y values [4, 5, 6] on ax2.

Matplotlib

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

fig = plt.figure(figsize=(8, 6))
gs = GridSpec(3, 3, figure=fig)

ax1 = fig.add_subplot(gs[0, :])
ax1.plot([0, 1, 2, 3], [10, 20, 25, 30])
# Your code here

Need a hint?

Use gs[2, 0] to select the bottom-left cell for the scatter plot.

4

Add a bar plot spanning the bottom-right two cells and display the figure

Create an axes called ax3 using fig.add_subplot(gs[2, 1:]) to span the bottom-right two cells. Plot a bar chart with categories ["A", "B", "C"] and values [5, 7, 3] on ax3. Finally, use plt.show() to display the figure.

Matplotlib

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

fig = plt.figure(figsize=(8, 6))
gs = GridSpec(3, 3, figure=fig)

ax1 = fig.add_subplot(gs[0, :])
ax1.plot([0, 1, 2, 3], [10, 20, 25, 30])

ax2 = fig.add_subplot(gs[2, 0])
ax2.scatter([1, 2, 3], [4, 5, 6])
# Your code here

Need a hint?

Use gs[2, 1:] to select the bottom-right two cells for the bar plot. Use plt.show() to display the figure.