Histogram vs bar chart distinction in Matplotlib - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a histogram of the data list using matplotlib.

Matplotlib

import matplotlib.pyplot as plt

data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
plt.[1](data)
plt.show()

Drag options to blanks, or click blank then click option'

Ahist

Bbar

Cplot

Dscatter

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'bar' instead of 'hist' will create a bar chart, not a histogram.

Using 'plot' or 'scatter' won't group data into bins.

The hist function creates a histogram, which groups data into bins and shows frequency.

2fill in blank

medium

Complete the code to create a bar chart showing counts of categories using matplotlib.

Matplotlib

import matplotlib.pyplot as plt

categories = ['A', 'B', 'C']
counts = [5, 7, 3]
plt.[1](categories, counts)
plt.show()

Drag options to blanks, or click blank then click option'

Ascatter

Bhist

Cbar

Dplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'hist' will try to bin numeric data, not suitable for categories.

Using 'scatter' or 'plot' won't create bars.

The bar function creates a bar chart, which shows counts or values for categories.

3fill in blank

hard

Fix the error in the code to correctly plot a histogram of the data.

Matplotlib

import matplotlib.pyplot as plt

data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
plt.hist(data, bins=[1])
plt.show()

Drag options to blanks, or click blank then click option'

A5

BNone

C[5]

D'5'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing bins as a string like '5' causes a TypeError.

Passing bins as a list like [5] is invalid.

The bins parameter expects an integer number of bins, not a string or list.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that counts how many times each number appears in the list.

Matplotlib

data = [1, 2, 2, 3, 3, 3]
counts = {num: data.[1](num) for num in [2](data)}

Drag options to blanks, or click blank then click option'

Acount

Blen

Cset

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using len instead of count causes errors.

Using list instead of set causes duplicate keys.

The count method counts occurrences of each number, and set gets unique numbers.

5fill in blank

hard

Fill all three blanks to create a bar chart showing counts of unique items from data.

Matplotlib

import matplotlib.pyplot as plt

data = ['apple', 'banana', 'apple', 'orange', 'banana', 'banana']
counts = {item: data.count(item) for item in [1](data)}
plt.bar(counts.[2](), counts.[3]())
plt.show()

Drag options to blanks, or click blank then click option'

Aset

Bvalues

Ckeys

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using list instead of set causes duplicate bars.

Swapping keys() and values() causes wrong axes.

set gets unique items, keys() gets the categories for x-axis, and values() gets counts for y-axis.

Practice

1. Which of the following best describes a histogram in matplotlib?

easy

A. It groups continuous data into ranges and shows frequency with touching bars.

B. It compares values across distinct categories with spaced bars.

C. It shows data points connected by lines.

D. It displays data as pie slices representing proportions.

Solution

1. Step 1: Understand histogram purpose

   A histogram groups continuous data into intervals (bins) and shows how many data points fall into each bin.

2. Step 2: Identify visual style

   Histograms have bars that touch each other to indicate continuous ranges.

3. Final Answer:

   It groups continuous data into ranges and shows frequency with touching bars. -> Option A

4. Quick Check:

   Histogram = continuous data + touching bars [OK]

Hint: Histograms group continuous data with touching bars [OK]

Common Mistakes:

• Confusing histograms with bar charts
• Thinking bars are spaced in histograms
• Assuming histograms show categories

2. Which matplotlib function is used to create a bar chart?

easy

A. plt.hist()

B. plt.bar()

C. plt.plot()

D. plt.scatter()

Solution

1. Step 1: Recall function for bar charts

   Matplotlib uses plt.bar() to create bar charts that compare categories.

2. Step 2: Differentiate from histogram function

   plt.hist() is for histograms, not bar charts.

3. Final Answer:

   plt.bar() -> Option B

4. Quick Check:

   Bar chart function = plt.bar() [OK]

Hint: Bar charts use plt.bar(), histograms use plt.hist() [OK]

Common Mistakes:

• Using plt.hist() for bar charts
• Confusing plt.plot() with bar charts
• Trying plt.scatter() for bar charts

3. What will be the visual difference between these two plots?

plt.hist([1,2,2,3,3,3,4])
plt.bar(['A','B','C'], [5,3,6])

medium

A. Histogram bars touch; bar chart bars have spaces between categories.

B. Both have spaced bars representing categories.

C. Bar chart bars touch; histogram bars have spaces.

D. Both have touching bars representing continuous data.

Solution

1. Step 1: Analyze histogram bars

   Histogram bars touch because they represent continuous data ranges.

2. Step 2: Analyze bar chart bars

   Bar chart bars are spaced because they represent distinct categories.

3. Final Answer:

   Histogram bars touch; bar chart bars have spaces between categories. -> Option A

4. Quick Check:

   Touching bars = histogram, spaced bars = bar chart [OK]

Hint: Touching bars = histogram; spaced bars = bar chart [OK]

Common Mistakes:

• Thinking bar charts have touching bars
• Assuming histograms have spaced bars
• Mixing continuous and categorical data visuals

4. Identify the error in this code snippet intended to plot a histogram:

import matplotlib.pyplot as plt
plt.bar([1,2,3,4], [5,6,7,8])
plt.show()

medium

A. No error; this correctly plots a histogram.

B. plt.show() is missing to display the plot.

C. Data lists have different lengths causing an error.

D. plt.bar() is used instead of plt.hist() for histogram plotting.

Solution

1. Step 1: Check function used for histogram

   plt.bar() creates bar charts, not histograms.

2. Step 2: Correct function for histogram

   Use plt.hist() to plot histograms of continuous data.

3. Final Answer:

   plt.bar() is used instead of plt.hist() for histogram plotting. -> Option D

4. Quick Check:

   Histogram needs plt.hist(), not plt.bar() [OK]

Hint: Use plt.hist() for histograms, not plt.bar() [OK]

Common Mistakes:

• Using plt.bar() to plot histograms
• Forgetting plt.show() to display plots
• Mismatched data lengths (not in this case)

5. You have a dataset of exam scores (0-100) and student majors (Math, History, Science). You want to show the distribution of scores and compare average scores by major. Which matplotlib plots should you use?

hard

A. Use two histograms: one for scores and one for majors.

B. Use a bar chart for scores distribution and a histogram for average scores by major.

C. Use a histogram for scores distribution and a bar chart for average scores by major.

D. Use two bar charts: one for scores and one for majors.

Solution

1. Step 1: Choose plot for continuous data (scores)

   Scores are continuous; use a histogram to show their distribution.

2. Step 2: Choose plot for categorical comparison (majors)

   Majors are categories; use a bar chart to compare average scores by major.

3. Final Answer:

   Use a histogram for scores distribution and a bar chart for average scores by major. -> Option C

4. Quick Check:

   Continuous data = histogram, categories = bar chart [OK]

Hint: Histogram for continuous, bar chart for categories [OK]

Common Mistakes:

• Using bar chart for continuous data distribution
• Using histogram for categorical averages
• Mixing plot types incorrectly