Horizontal bar chart with plt.barh in Matplotlib - Time & Space Complexity

Time Complexity: Horizontal bar chart with plt.barh

O(n)

Understanding Time Complexity

We want to understand how the time to draw a horizontal bar chart changes as we add more bars.

How does the work grow when the number of bars increases?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt

labels = ['A', 'B', 'C', 'D', 'E']
values = [5, 7, 3, 8, 4]

plt.barh(labels, values)
plt.show()

This code draws a horizontal bar chart with 5 bars labeled A to E with given values.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Drawing each bar on the chart.
• How many times: Once for each label and value pair (here 5 times).

How Execution Grows With Input

As the number of bars increases, the drawing work grows linearly.

Input Size (n)	Approx. Operations
10	10 drawing steps
100	100 drawing steps
1000	1000 drawing steps

Pattern observation: Doubling the bars doubles the drawing work.

Final Time Complexity

Time Complexity: O(n)

This means the time to draw the chart grows directly with the number of bars.

Common Mistake

[X] Wrong: "Drawing a bar chart takes the same time no matter how many bars there are."

[OK] Correct: Each bar needs to be drawn separately, so more bars mean more work.

Interview Connect

Understanding how drawing time grows helps you explain performance when visualizing data with many points.

Self-Check

What if we added nested loops to draw grouped bars? How would the time complexity change?

Practice

1. What does the plt.barh() function in matplotlib do?

easy

A. Generates a scatter plot with dots

B. Creates a vertical bar chart with bars extending bottom to top

C. Creates a horizontal bar chart with bars extending left to right

D. Plots a line graph connecting data points

Solution

1. Step 1: Understand the function purpose

   plt.barh() is designed to create horizontal bar charts, where bars extend from left to right.

2. Step 2: Compare with other plot types

   Vertical bar charts use plt.bar(), line graphs use plt.plot(), and scatter plots use plt.scatter().

3. Final Answer:

   Creates a horizontal bar chart with bars extending left to right -> Option C

4. Quick Check:

   Horizontal bar chart = plt.barh() [OK]

Hint: Remember 'h' in barh means horizontal bars [OK]

Common Mistakes:

• Confusing plt.barh() with plt.bar()
• Thinking plt.barh() creates vertical bars
• Mixing bar charts with line or scatter plots

2. Which of the following is the correct syntax to create a horizontal bar chart with categories ['A', 'B', 'C'] and values [5, 7, 3] using matplotlib?

easy

A. plt.barh(['A', 'B', 'C'], [5, 7, 3])

B. plt.bar([5, 7, 3], ['A', 'B', 'C'])

C. plt.barh([5, 7, 3], ['A', 'B', 'C'])

D. plt.plot(['A', 'B', 'C'], [5, 7, 3])

Solution

1. Step 1: Identify correct function and argument order

   plt.barh() takes categories as the first argument (y-axis labels) and values as the second argument (bar lengths).

2. Step 2: Check each option

   plt.barh(['A', 'B', 'C'], [5, 7, 3]) correctly uses plt.barh(['A', 'B', 'C'], [5, 7, 3]). plt.bar([5, 7, 3], ['A', 'B', 'C']) uses vertical bars and reverses arguments. plt.barh([5, 7, 3], ['A', 'B', 'C']) reverses arguments for horizontal bars. plt.plot(['A', 'B', 'C'], [5, 7, 3]) plots a line graph.

3. Final Answer:

   plt.barh(['A', 'B', 'C'], [5, 7, 3]) -> Option A

4. Quick Check:

   Categories first, values second in plt.barh() [OK]

Hint: In plt.barh(), categories come first, then values [OK]

Common Mistakes:

• Swapping categories and values in arguments
• Using plt.bar() instead of plt.barh() for horizontal bars
• Using plt.plot() instead of bar chart functions

3. What will be the output of the following code?

import matplotlib.pyplot as plt
categories = ['X', 'Y', 'Z']
values = [10, 5, 8]
plt.barh(categories, values, color='green')
plt.show()

medium

A. A vertical bar chart with green bars for categories X, Y, Z

B. A line plot connecting points (X,10), (Y,5), (Z,8)

C. An error because color must be a list

D. A horizontal bar chart with green bars for categories X, Y, Z

Solution

1. Step 1: Analyze the function and parameters

   The code uses plt.barh() with categories on y-axis and values as bar lengths, colored green.

2. Step 2: Understand the plot output

   This produces a horizontal bar chart with green bars labeled X, Y, Z with lengths 10, 5, and 8 respectively.

3. Final Answer:

   A horizontal bar chart with green bars for categories X, Y, Z -> Option D

4. Quick Check:

   plt.barh() + color='green' = horizontal green bars [OK]

Hint: plt.barh() always creates horizontal bars, color accepts string [OK]

Common Mistakes:

• Thinking plt.barh() creates vertical bars
• Assuming color must be a list
• Confusing bar chart with line plot

4. Identify the error in this code snippet that tries to create a horizontal bar chart:

import matplotlib.pyplot as plt
labels = ['A', 'B', 'C']
values = [4, 6, 8]
plt.barh(values, labels)
plt.show()

medium

A. plt.barh() does not accept lists as arguments

B. Arguments are reversed; categories should be first, values second

C. Missing plt.show() call

D. Color argument is required for plt.barh()

Solution

1. Step 1: Check argument order in plt.barh()

   The first argument should be categories (labels), the second argument should be values (bar lengths).

2. Step 2: Identify the mistake in the code

   The code passes values first and labels second, which reverses the expected order and causes incorrect plotting.

3. Final Answer:

   Arguments are reversed; categories should be first, values second -> Option B

4. Quick Check:

   plt.barh(categories, values) order matters [OK]

Hint: Categories first, values second in plt.barh() [OK]

Common Mistakes:

• Swapping the order of categories and values
• Forgetting plt.show() (though present here)
• Thinking color argument is mandatory

5. You have a dataset with categories ['Jan', 'Feb', 'Mar'] and sales [200, 150, 300]. You want to create a horizontal bar chart with red bars, bar height of 0.5, and display the sales values on the bars. Which code snippet correctly achieves this?

hard

A. plt.barh(['Jan', 'Feb', 'Mar'], [200, 150, 300], color='red', height=0.5)
for i, v in enumerate([200, 150, 300]):
plt.text(v + 5, i, str(v))
plt.show()

B. plt.barh([200, 150, 300], ['Jan', 'Feb', 'Mar'], color='red', height=0.5)
plt.show()

C. plt.bar(['Jan', 'Feb', 'Mar'], [200, 150, 300], color='red', height=0.5)
plt.show()

D. plt.barh(['Jan', 'Feb', 'Mar'], [200, 150, 300], color='red', width=0.5)
plt.show()

Solution

1. Step 1: Use plt.barh() with correct arguments

   Categories come first, then values. Set color='red' and height=0.5 to adjust bar thickness.

2. Step 2: Add sales values as text labels on bars

   Use a for loop with plt.text() to place sales numbers slightly right of each bar end.

3. Step 3: Verify other options

   plt.barh([200, 150, 300], ['Jan', 'Feb', 'Mar'], color='red', height=0.5) plt.show() reverses arguments, plt.bar(['Jan', 'Feb', 'Mar'], [200, 150, 300], color='red', height=0.5) plt.show() uses vertical bars, plt.barh(['Jan', 'Feb', 'Mar'], [200, 150, 300], color='red', width=0.5) plt.show() uses 'width' instead of 'height' which is invalid for barh.

4. Final Answer:

   plt.barh(['Jan', 'Feb', 'Mar'], [200, 150, 300], color='red', height=0.5) for i, v in enumerate([200, 150, 300]): plt.text(v + 5, i, str(v)) plt.show() -> Option A

5. Quick Check:

   plt.barh(categories, values, height=0.5) + plt.text() labels [OK]

Hint: Use height for bar thickness in plt.barh(), add labels with plt.text() [OK]

Common Mistakes:

• Swapping categories and values
• Using width instead of height for bar thickness
• Not adding text labels or placing them incorrectly