Marker size variation in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does changing the marker size in a matplotlib scatter plot do?

Changing the marker size makes the points on the plot bigger or smaller, helping to show differences or importance visually.

beginner

How do you set a fixed marker size in matplotlib's scatter plot?

Use the 's' parameter in plt.scatter(), like plt.scatter(x, y, s=50), where 50 is the size of each marker.

intermediate

Can marker sizes vary for each point in a scatter plot? How?

Yes, by passing a list or array of sizes to the 's' parameter, each point can have a different size.

intermediate

What unit is used for marker size in matplotlib scatter plots?

Marker size is in points squared (pt²), so size 100 means the marker area is 100 points squared.

beginner

Why might you want to vary marker sizes in a scatter plot?

To show extra information like quantity or importance, making the plot easier to understand at a glance.

Which parameter controls marker size in matplotlib's scatter plot?

A size

B marker

C s

D ms

The 's' parameter sets the marker size in plt.scatter().

What happens if you pass a list of sizes to the 's' parameter?

A All markers get the same size

B Each marker gets a size from the list

C Markers become invisible

D An error occurs

Passing a list lets each marker have its own size.

If you want bigger markers, you should:

A Decrease the 's' value

B Use a different color

C Change the marker shape

D Increase the 's' value

Increasing 's' makes markers bigger.

Marker size in matplotlib scatter plots is measured in:

A Points squared

B Inches

C Pixels

D Centimeters

Marker size uses points squared as units.

Why use different marker sizes in a scatter plot?

A To show extra data dimensions

B To add color variety

C To change marker shape

D To make the plot smaller

Different sizes can represent extra data like quantity.

Explain how to vary marker sizes in a matplotlib scatter plot and why it might be useful.

Think about how size can represent importance or quantity.

Describe the unit of marker size in matplotlib and how changing it affects the plot.

Consider how size relates to the area of the marker.

Practice

1. What does the s parameter control in the plt.scatter() function in matplotlib?

easy

A. The size of the markers in the scatter plot

B. The color of the markers

C. The shape of the markers

D. The transparency of the markers

Solution

1. Step 1: Understand the role of plt.scatter()

   The plt.scatter() function creates scatter plots where each point can have different visual properties.

2. Step 2: Identify the s parameter purpose

   The s parameter specifically sets the size of each marker in the scatter plot, either as a single value or a list of sizes.

3. Final Answer:

   The size of the markers in the scatter plot -> Option A

4. Quick Check:

   s controls marker size [OK]

Hint: Remember: 's' stands for size in scatter plots [OK]

Common Mistakes:

• Confusing 's' with color or shape parameters
• Thinking 's' controls transparency
• Assuming 's' changes marker style

2. Which of the following is the correct way to set marker sizes to 50 for all points in a scatter plot using matplotlib?

easy

A. plt.scatter(x, y, size=50)

B. plt.scatter(x, y, s=50)

C. plt.scatter(x, y, marker_size=50)

D. plt.scatter(x, y, sizes=50)

Solution

1. Step 1: Recall the parameter name for marker size

   The correct parameter to set marker size in plt.scatter() is s.

2. Step 2: Check the syntax for setting size

   Using s=50 sets all markers to size 50. Other options use incorrect parameter names.

3. Final Answer:

   plt.scatter(x, y, s=50) -> Option B

4. Quick Check:

   Use s for size [OK]

Hint: Use s to set size, not 'size' or 'sizes' [OK]

Common Mistakes:

• Using 'size' or 'sizes' instead of 's'
• Trying to set marker size with 'marker_size'
• Syntax errors from wrong parameter names

3. What will be the output marker sizes for the scatter plot from this code?

import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [4, 5, 6]
sizes = [20, 50, 80]
plt.scatter(x, y, s=sizes)
plt.show()

medium

A. All markers will have size 20

B. Code will raise an error due to wrong size input

C. Markers will have default size because list is invalid

D. Markers will have sizes 20, 50, and 80 respectively

Solution

1. Step 1: Understand s with list input

   The s parameter accepts a list to assign different sizes to each marker.

2. Step 2: Match sizes to points

   Since sizes = [20, 50, 80], the first point gets size 20, second 50, third 80.

3. Final Answer:

   Markers will have sizes 20, 50, and 80 respectively -> Option D

4. Quick Check:

   List in s sets sizes per point [OK]

Hint: List in s sets sizes point-wise [OK]

Common Mistakes:

• Assuming all markers get the first size
• Thinking list input causes error
• Confusing s with color list

4. Identify the error in this code snippet that tries to vary marker sizes:

import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [4, 5, 6]
sizes = [30, 60]
plt.scatter(x, y, s=sizes)
plt.show()

medium

A. The plt.scatter function is misspelled

B. The s parameter cannot accept lists

C. The sizes list length does not match x and y length

D. The variable sizes is not defined

Solution

1. Step 1: Check lengths of data and sizes

   The x and y lists have 3 points, but sizes list has only 2 values.

2. Step 2: Understand size list requirement

   The s list must match the number of points; otherwise, matplotlib raises a ValueError.

3. Final Answer:

   The sizes list length does not match x and y length -> Option C

4. Quick Check:

   Sizes list length must equal data points [OK]

Hint: Match sizes list length to data points [OK]

Common Mistakes:

• Ignoring size list length mismatch
• Thinking s can't be a list
• Assuming matplotlib auto-fills missing sizes

5. You want to create a scatter plot where marker sizes represent the population of cities. Given:

cities = ['A', 'B', 'C']
population = [1000, 5000, 3000]
x = [1, 2, 3]
y = [4, 5, 6]

Which code correctly scales the population to marker sizes and plots them?

hard

A. plt.scatter(x, y, s=[p*10 for p in population])

B. plt.scatter(x, y, s=[p/10 for p in population])

C. plt.scatter(x, y, s=population)

D. plt.scatter(x, y, s=[p**2 for p in population])

Solution

1. Step 1: Understand marker size scaling

   Population values are large; directly using them as sizes will create huge markers.

2. Step 2: Choose appropriate scaling

   Multiplying population by 10 scales sizes visibly but keeps them reasonable. Dividing by 10 makes markers too small; squaring makes them too large.

3. Final Answer:

   plt.scatter(x, y, s=[p*10 for p in population]) -> Option A

4. Quick Check:

   Scale sizes for visibility using multiplication [OK]

Hint: Scale data to reasonable marker sizes by multiplying [OK]

Common Mistakes:

• Using raw large values causing huge markers
• Dividing sizes too much making markers tiny
• Using squared sizes causing disproportionate markers