Named colors and hex codes in Matplotlib - Time & Space Complexity

Time Complexity: Named colors and hex codes

O(n)

Understanding Time Complexity

We want to understand how the time it takes to use named colors or hex codes in matplotlib changes as we add more colors.

How does the number of colors affect the drawing time?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt

colors = ['red', '#00FF00', 'blue', '#FF00FF', 'cyan']
for i, color in enumerate(colors):
    plt.plot([0, 1], [i, i], color=color)
plt.show()

This code draws several lines, each with a different color given by a named color or a hex code.

Identify Repeating Operations

• Primary operation: Looping over the list of colors to draw each line.
• How many times: Once for each color in the list.

How Execution Grows With Input

Each added color means one more line to draw, so the work grows steadily with the number of colors.

Input Size (n)	Approx. Operations
10	10 lines drawn
100	100 lines drawn
1000	1000 lines drawn

Pattern observation: The time grows directly in proportion to the number of colors.

Final Time Complexity

Time Complexity: O(n)

This means the time to draw grows in a straight line as you add more colors.

Common Mistake

[X] Wrong: "Using hex codes is slower than named colors because hex codes are longer strings."

[OK] Correct: Matplotlib treats both named colors and hex codes similarly internally, so the length of the color code does not affect drawing time noticeably.

Interview Connect

Understanding how the number of items affects drawing time helps you reason about performance in data visualization tasks, a useful skill in many projects.

Self-Check

What if we changed the code to draw multiple lines per color? How would the time complexity change?

Practice

1. Which of the following is a valid named color in matplotlib?

easy

A. #12345G

B. bluish

C. red

D. 123456

Solution

1. Step 1: Understand named colors in matplotlib

   Matplotlib supports standard color names like 'red', 'blue', 'green', etc.

2. Step 2: Check each option

   red is 'red', a valid named color. #12345G has an invalid hex code with 'G'. bluish 'bluish' is not a recognized name. 123456 is just digits, not a named color.

3. Final Answer:

   red -> Option C

4. Quick Check:

   Named color 'red' is valid [OK]

Hint: Named colors are simple words like 'red' or 'blue' [OK]

Common Mistakes:

• Confusing invalid hex codes as named colors
• Assuming any color-like word is valid
• Using numbers without '#' as colors

2. Which of the following is the correct way to specify a hex color code in matplotlib?

easy

A. "#1a2b3c"

B. "1a2b3c"

C. "#12345"

D. "#xyz123"

Solution

1. Step 1: Recall hex color code format

   Hex codes start with '#' followed by exactly 6 hexadecimal digits (0-9, a-f).

2. Step 2: Validate each option

   "#1a2b3c" has '#' and 6 valid hex digits. "1a2b3c" misses '#'. "#12345" has only 5 digits. "#xyz123" contains invalid letters 'x' and 'z'.

3. Final Answer:

   "#1a2b3c" -> Option A

4. Quick Check:

   Hex code must start with '#' and have 6 hex digits [OK]

Hint: Hex codes start with '#' and have 6 hex digits [OK]

Common Mistakes:

• Omitting the '#' symbol
• Using wrong number of digits
• Including invalid characters

3. What color will the following matplotlib code produce?

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], color="#00FF00")
plt.show()

medium

A. Black

B. Blue

C. Red

D. Green

Solution

1. Step 1: Understand the hex code used

   "#00FF00" is a hex code where red=00, green=FF, blue=00, meaning full green.

2. Step 2: Match hex code to color

   Since green is max and others zero, the line color will be bright green.

3. Final Answer:

   Green -> Option D

4. Quick Check:

   "#00FF00" means green color [OK]

Hint: Hex #00FF00 means full green, no red or blue [OK]

Common Mistakes:

• Confusing hex digits order
• Assuming #00FF00 is blue
• Ignoring case sensitivity in hex

4. Identify the error in this matplotlib color specification:

plt.plot([1, 2, 3], color="#123ABZ")

medium

A. Missing '#' in hex code

B. Invalid hex code due to 'Z'

C. Color name not recognized

D. Syntax error in plot function

Solution

1. Step 1: Check hex code characters

   Hex codes only allow digits 0-9 and letters A-F (case insensitive). 'Z' is invalid.

2. Step 2: Confirm error type

   The code has '#' and correct length, but 'Z' makes it invalid hex code.

3. Final Answer:

   Invalid hex code due to 'Z' -> Option B

4. Quick Check:

   Hex digits must be 0-9 or A-F only [OK]

Hint: Hex codes only use digits 0-9 and letters A-F [OK]

Common Mistakes:

• Ignoring invalid characters in hex
• Confusing missing '#' with invalid chars
• Assuming any letter is allowed in hex

5. You want to plot two lines in matplotlib: one red and one with a custom color #FF8800. Which code snippet correctly sets these colors?

hard

A. plt.plot(x, y1, color='red')
plt.plot(x, y2, color='#FF8800')

B. plt.plot(x, y1, color='#red')
plt.plot(x, y2, color='FF8800')

C. plt.plot(x, y1, color='ff8800')
plt.plot(x, y2, color='red')

D. plt.plot(x, y1, color='red')
plt.plot(x, y2, color='FF8800')

Solution

1. Step 1: Check named color usage

   Named colors like 'red' are used as strings without '#'. Adding '#' to named colors makes them invalid.

2. Step 2: Check hex code usage

   Hex codes must start with '#'. Omitting '#' for hex colors like 'FF8800' or using lowercase without '#' is invalid.

3. Final Answer:

   plt.plot(x, y1, color='red') plt.plot(x, y2, color='#FF8800') -> Option A

4. Quick Check:

   Named colors no '#', hex codes start with '#' [OK]

Hint: Named colors no '#'; hex codes start with '#' [OK]

Common Mistakes:

• Adding '#' to named colors
• Omitting '#' in hex codes
• Using lowercase hex without '#'