Bar chart color customization in Matplotlib - Step-by-Step Execution

Concept Flow - Bar chart color customization

Start

↓

Prepare data

↓

Choose colors

↓

Create bar chart with colors

↓

Display chart

↓

End

This flow shows how to prepare data, select colors, create a bar chart with those colors, and display it.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt

labels = ['A', 'B', 'C']
values = [5, 7, 3]
colors = ['red', 'green', 'blue']

plt.bar(labels, values, color=colors)
plt.show()

This code draws a bar chart with three bars, each having a different color.

Execution Table

Step	Action	Variables	Result
1	Import matplotlib.pyplot as plt	plt imported	Ready to plot
2	Define labels	labels = ['A', 'B', 'C']	Labels set
3	Define values	values = [5, 7, 3]	Values set
4	Define colors	colors = ['red', 'green', 'blue']	Colors set
5	Call plt.bar(labels, values, color=colors)	labels, values, colors	Bar chart created with colored bars
6	Call plt.show()	None	Chart displayed on screen
7	End of script	None	Execution stops

💡 Script ends after displaying the colored bar chart

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	Final
labels	None	['A', 'B', 'C']	['A', 'B', 'C']	['A', 'B', 'C']	['A', 'B', 'C']
values	None	None	[5, 7, 3]	[5, 7, 3]	[5, 7, 3]
colors	None	None	None	['red', 'green', 'blue']	['red', 'green', 'blue']

Key Moments - 2 Insights

Why do we pass a list of colors instead of a single color string?

Because each bar can have its own color, passing a list assigns colors to bars one by one as shown in step 5 of the execution_table.

What happens if the colors list is shorter than the number of bars?

Matplotlib will repeat colors or use default colors for remaining bars. This is not shown here but relates to how colors list matches labels length in step 4.

Visual Quiz - 3 Questions

Look at the execution_table, what is the value of 'colors' after step 4?

A ['A', 'B', 'C']

B ['red', 'green', 'blue']

C [5, 7, 3]

D None

💡 Hint

Check the 'Variables' column in row with Step 4 in execution_table

At which step is the bar chart actually created with colors?

A Step 2

B Step 6

C Step 5

D Step 3

💡 Hint

Look for the action mentioning plt.bar in execution_table

If we change colors to ['yellow', 'purple', 'cyan'], what changes in the execution_table?

A Only the 'colors' variable value in Step 4 changes

B The bar chart creation step changes to use different function

C The labels variable changes

D No changes at all

💡 Hint

Colors list is defined in Step 4, check variable_tracker for colors

Concept Snapshot

Bar chart color customization:
- Use plt.bar(x, height, color=colors)
- colors can be a single color or list of colors
- List assigns colors to bars in order
- plt.show() displays the chart
- Colors must match number of bars for best results

Full Transcript

This example shows how to customize bar colors in a matplotlib bar chart. We start by importing matplotlib.pyplot as plt. Then we define three labels and their corresponding values. Next, we create a list of colors, one for each bar. We call plt.bar with labels, values, and the colors list to create the bar chart. Finally, plt.show() displays the chart with each bar colored as specified. Variables labels, values, and colors are set step by step. The key moment is understanding that the colors list assigns colors to bars one by one. The execution table traces each step from import to display. The quiz checks understanding of variable values and steps where actions happen.