Colorbar formatting in Matplotlib - Step-by-Step Execution

Concept Flow - Colorbar formatting

Create plot with data

↓

Add colorbar to plot

↓

Set colorbar label

↓

Format ticks (size, color, rotation)

↓

Adjust colorbar limits and ticks

↓

Display formatted colorbar

The flow shows creating a plot, adding a colorbar, then formatting its label, ticks, and limits before displaying.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

img = plt.imshow(np.random.rand(5,5))
cbar = plt.colorbar(img)
cbar.set_label('Intensity')
cbar.ax.tick_params(labelsize=10, labelcolor='red', rotation=45)
plt.show()

This code creates a heatmap, adds a colorbar with a label, formats tick labels, and shows the plot.

Execution Table

Step	Action	Effect on Colorbar	Output/State
1	Create heatmap with random data	No colorbar yet	Plot with colored grid created
2	Add colorbar linked to heatmap	Colorbar appears with default ticks and label	Colorbar added on side with default settings
3	Set colorbar label to 'Intensity'	Label text added beside colorbar	Label 'Intensity' set
4	Format tick labels: size=10, color=red, rotation=45	Tick labels change style	Ticks formatted: rotated 45°, red color, font size 10
5	Display plot	Final visual with formatted colorbar	Plot window with heatmap and formatted colorbar

💡 Plot displayed with formatted colorbar; execution ends.

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	Final
img	None	AxesImage object created	AxesImage unchanged	AxesImage unchanged	AxesImage unchanged
cbar	None	Colorbar object created	Label set to 'Intensity'	Tick params updated (size=10, color=red, rotation=45)	Formatted colorbar displayed

Key Moments - 2 Insights

Why do tick labels on the colorbar rotate but the colorbar itself does not?

Because only the tick labels' properties are changed using tick_params (rotation=45), not the colorbar axis or the colorbar itself. See execution_table step 4.

What happens if you set the colorbar label before adding the colorbar?

You cannot set the label before creating the colorbar object. The label is a property of the colorbar, so it must exist first (see step 2 then step 3).

Visual Quiz - 3 Questions

Look at the execution table, what is the color of the tick labels after step 4?

A Blue

B Red

C Black

D Green

💡 Hint

Check the 'Effect on Colorbar' column in step 4 describing tick label formatting.

At which step is the colorbar label set to 'Intensity'?

A Step 3

B Step 2

C Step 4

D Step 5

💡 Hint

Look at the 'Action' column for setting the label text.

If you skip step 4, how would the colorbar ticks appear?

A Rotated 45 degrees and red

B No ticks shown

C Default orientation and color

D Ticks with label 'Intensity'

💡 Hint

Refer to the 'Effect on Colorbar' column in step 2 and 3 where ticks are default before formatting.

Concept Snapshot

Colorbar formatting in matplotlib:
- Add colorbar with plt.colorbar()
- Set label with cbar.set_label('text')
- Format ticks with cbar.ax.tick_params(labelsize=, labelcolor=, rotation=)
- Adjust limits and ticks with cbar.set_ticks() or cbar.set_clim()
- Display plot with plt.show()

Full Transcript

This visual execution traces how to format a colorbar in matplotlib. First, a heatmap is created with random data. Then a colorbar is added linked to the heatmap. Next, the colorbar label is set to 'Intensity'. After that, tick labels on the colorbar are formatted to have font size 10, red color, and rotated 45 degrees. Finally, the plot is displayed showing the heatmap with the formatted colorbar. Variables img and cbar track the image and colorbar objects respectively. Key moments clarify that only tick labels rotate, not the colorbar itself, and that the colorbar must exist before setting its label. The quiz tests understanding of tick label color, label setting step, and default tick appearance if formatting is skipped.