Font properties customization in Matplotlib - Time & Space Complexity

Time Complexity: Font properties customization

O(n)

Understanding Time Complexity

When customizing font properties in matplotlib, it's important to understand how the time to render text changes as we add more text elements or customize more properties.

We want to know how the execution time grows when we change font settings for multiple text items.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties

fig, ax = plt.subplots()
font = FontProperties(family='serif', style='italic', size=12)
n = 10
for i in range(n):
    ax.text(0.5, i*0.1, f'Text {i}', fontproperties=font)
plt.show()

This code creates a plot and adds n text labels with customized font properties.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Adding text labels with font customization inside a loop.
• How many times: The loop runs n times, once for each text label.

How Execution Grows With Input

Each new text label requires setting font properties and rendering, so the total work grows as we add more labels.

Input Size (n)	Approx. Operations
10	10 font setups and text renders
100	100 font setups and text renders
1000	1000 font setups and text renders

Pattern observation: The execution time grows roughly in direct proportion to the number of text items.

Final Time Complexity

Time Complexity: O(n)

This means the time to customize and render fonts grows linearly with the number of text elements.

Common Mistake

[X] Wrong: "Customizing font properties once will speed up adding all text labels."

[OK] Correct: Each text label needs its own font setup and rendering, so the work adds up with more labels.

Interview Connect

Understanding how rendering time grows with more customized text helps you explain performance in data visualization tasks clearly and confidently.

Self-Check

What if we reused the same font properties object without creating a new one inside the loop? How would the time complexity change?

Practice

1. Which font property controls the thickness of the text in a matplotlib plot?

easy

A. family

B. size

C. weight

D. color

Solution

1. Step 1: Understand font properties

   Font properties include size, weight, family, style, and color.

2. Step 2: Identify the property for thickness

   The thickness or boldness of text is controlled by the 'weight' property.

3. Final Answer:

   weight -> Option C

4. Quick Check:

   Font thickness = weight [OK]

Hint: Thickness means weight in font properties [OK]

Common Mistakes:

• Confusing size with weight
• Thinking color controls thickness
• Mixing family with weight

2. Which of the following is the correct way to set the font size of a plot title to 16 using fontdict in matplotlib?

easy

A. plt.title('My Title', font={'fontsize':16})

B. plt.title('My Title', fontdict={'size':16})

C. plt.title('My Title', font={'size':16})

D. plt.title('My Title', fontdict={'fontsize':16})

Solution

1. Step 1: Recall fontdict usage

   In matplotlib, fontdict keys include 'size' for font size, not 'fontsize'.

2. Step 2: Check correct syntax

   Using fontdict={'size':16} correctly sets font size to 16.

3. Final Answer:

   plt.title('My Title', fontdict={'size':16}) -> Option B

4. Quick Check:

   fontdict uses 'size' key [OK]

Hint: Use 'size' key inside fontdict for font size [OK]

Common Mistakes:

• Using 'fontsize' instead of 'size'
• Using 'font' instead of 'fontdict'
• Wrong dictionary key names

3. What will be the font size of the x-axis label in the following code?

import matplotlib.pyplot as plt
plt.xlabel('X Axis', fontdict={'size':20, 'weight':'bold'})
plt.show()

medium

A. 20

B. Bold but default size

C. Default size (usually 10)

D. Error due to wrong fontdict

Solution

1. Step 1: Analyze fontdict in xlabel

   The fontdict sets 'size' to 20 and 'weight' to 'bold'.

2. Step 2: Understand effect on label

   The label will use size 20 and bold weight as specified.

3. Final Answer:

   20 -> Option A

4. Quick Check:

   fontdict size = 20 [OK]

Hint: fontdict size sets label font size directly [OK]

Common Mistakes:

• Assuming default size
• Ignoring weight property
• Thinking code causes error

4. Identify the error in this code snippet that tries to set the legend font to italic:

import matplotlib.pyplot as plt
plt.plot([1,2,3], label='Line')
plt.legend(prop={'style':'italic'})
plt.show()

medium

A. Missing plt.legend() call

B. No error, code runs fine

C. Incorrect label argument in plot

D. 'style' is not a valid font property key for legend prop

Solution

1. Step 1: Check font property keys for legend

   Valid keys include 'size', 'weight', 'family', 'style', and 'color'. 'style' is valid but must be a recognized value.

2. Step 2: Verify 'italic' usage

   'italic' is a valid style, so the key is correct. However, in matplotlib, 'style' should be set inside a FontProperties object or as a string, not directly in prop dict.

3. Step 3: Identify actual error

   The error is that 'prop' expects a FontProperties object or a dictionary with correct keys, but 'style' key is not always recognized directly in prop dict in some matplotlib versions.

4. Final Answer:

   'style' is not a valid font property key for legend prop -> Option D

5. Quick Check:

   Legend prop keys must be valid font properties [OK]

Hint: Use FontProperties for complex font styles in legend [OK]

Common Mistakes:

• Using wrong keys in prop dict
• Forgetting to import FontProperties
• Assuming all keys work directly

5. You want to create a plot with a title that uses a custom font family 'Comic Sans MS', size 18, bold weight, and blue color. Which code snippet correctly applies all these font properties?

hard

A. plt.title('My Plot', fontdict={'family':'Comic Sans MS', 'size':18, 'weight':'bold', 'color':'blue'})

B. plt.title('My Plot', fontdict={'fontfamily':'Comic Sans MS', 'fontsize':18, 'fontweight':'bold', 'fontcolor':'blue'})

C. plt.title('My Plot', font={'family':'Comic Sans MS', 'size':18, 'weight':'bold', 'color':'blue'})

D. plt.title('My Plot', fontdict={'family':'Comic Sans MS', 'fontsize':18, 'weight':'bold', 'color':'blue'})

Solution

1. Step 1: Check correct fontdict keys

   Valid keys are 'family', 'size', 'weight', and 'color'. 'fontsize' and 'fontweight' are incorrect keys here.

2. Step 2: Verify values and syntax

   plt.title('My Plot', fontdict={'family':'Comic Sans MS', 'size':18, 'weight':'bold', 'color':'blue'}) uses correct keys and values for family, size, weight, and color.

3. Final Answer:

   plt.title('My Plot', fontdict={'family':'Comic Sans MS', 'size':18, 'weight':'bold', 'color':'blue'}) -> Option A

4. Quick Check:

   Use 'family', 'size', 'weight', 'color' keys in fontdict [OK]

Hint: Use standard keys: family, size, weight, color in fontdict [OK]

Common Mistakes:

• Using 'fontsize' instead of 'size'
• Using 'fontcolor' instead of 'color'
• Passing fontdict as 'font'