Marker size variation in Matplotlib - Step-by-Step Execution

Concept Flow - Marker size variation

Start

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Define data points

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Define marker sizes

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Call scatter plot with sizes

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Plot displays with varied marker sizes

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End

This flow shows how data points and their marker sizes are defined, then plotted with varying sizes using scatter.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
sizes = [20, 50, 80, 200]
plt.scatter(x, y, s=sizes)
plt.show()

Plot 4 points with marker sizes varying as per the sizes list.

Execution Table

Step	Variable/Action	Value/Description	Effect on Plot
1	x	[1, 2, 3, 4]	Defines x-coordinates of points
2	y	[10, 20, 25, 30]	Defines y-coordinates of points
3	sizes	[20, 50, 80, 200]	Defines marker sizes for each point
4	plt.scatter(x, y, s=sizes)	Scatter plot called with sizes	Points plotted with sizes 20, 50, 80, 200 respectively
5	plt.show()	Plot window opens	Visual display of points with varied marker sizes
6	End	-	Plotting complete

💡 All points plotted with specified sizes; execution ends after plot display

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
x	undefined	[1, 2, 3, 4]	[1, 2, 3, 4]	[1, 2, 3, 4]	[1, 2, 3, 4]
y	undefined	undefined	[10, 20, 25, 30]	[10, 20, 25, 30]	[10, 20, 25, 30]
sizes	undefined	undefined	undefined	[20, 50, 80, 200]	[20, 50, 80, 200]

Key Moments - 2 Insights

Why do marker sizes look different even though the points are plotted with the same x and y?

Because the 'sizes' list assigns different size values to each point, as shown in execution_table step 3 and 4, the scatter plot uses these sizes to vary marker sizes.

What happens if the sizes list has fewer elements than x and y?

Matplotlib will raise an error because each point needs a corresponding size. This is implied by the need for matching lengths in execution_table steps 1-4.

Visual Quiz - 3 Questions

Look at the execution_table at step 3, what does the 'sizes' variable represent?

A Sizes of markers for each point

B Coordinates of points on y-axis

C Coordinates of points on x-axis

D Colors of markers

💡 Hint

Refer to execution_table row with step 3 describing 'sizes' as marker sizes

At which step in the execution_table are the points actually drawn with varied sizes?

A Step 2

B Step 5

C Step 4

D Step 1

💡 Hint

Step 4 calls plt.scatter which plots points with sizes

If the sizes list was changed to [100, 100, 100, 100], how would the plot change?

A Points would disappear

B All points would have the same size

C Points would have random sizes

D Plot would show error

💡 Hint

Check variable_tracker for sizes and how it affects marker size in execution_table step 4

Concept Snapshot

Marker size variation in matplotlib scatter plot:
- Use 's' parameter to set marker sizes
- Provide a list of sizes matching data points
- Larger values mean bigger markers
- Sizes control visual emphasis of points
- Syntax: plt.scatter(x, y, s=sizes)

Full Transcript

This example shows how to vary marker sizes in a scatter plot using matplotlib. We define x and y coordinates for points, then create a sizes list with different values. Calling plt.scatter with s=sizes plots points with marker sizes matching the list. The execution table traces each step: defining variables, calling scatter, and showing the plot. Variable tracker shows how x, y, and sizes are set before plotting. Key moments clarify why sizes affect marker appearance and the importance of matching list lengths. The quiz tests understanding of sizes role, plotting step, and effect of uniform sizes. This helps beginners see how marker size variation works visually and step-by-step.