Cumulative histograms in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of cumulative histogram with uniform data

What is the output array of counts for the cumulative histogram of 10 numbers from 1 to 10 with 5 bins?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

data = np.arange(1, 11)
counts, bins, patches = plt.hist(data, bins=5, cumulative=True)
plt.close()
print(counts)

A [2. 3. 5. 7. 10.]

B [1. 2. 3. 4. 5.]

C [0. 2. 4. 6. 8.]

D [2. 4. 6. 8. 10.]

💡 Hint

Think about how cumulative counts add up across bins.

The data has 10 values evenly spaced from 1 to 10. With 5 bins, each bin covers 2 numbers. The cumulative counts add up the number of data points up to each bin edge, resulting in [2, 4, 6, 8, 10].

❓ data_output

intermediate

Number of bins in cumulative histogram

If you create a cumulative histogram with 7 bins from data of 50 random values, how many count values will the output array have?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

data = np.random.randn(50)
counts, bins, patches = plt.hist(data, bins=7, cumulative=True)
plt.close()
print(len(counts))

A 50

B 6

C 7

D 8

💡 Hint

The counts array length matches the number of bins.

The counts array length equals the number of bins specified, which is 7.

❓ visualization

advanced

Identify the cumulative histogram plot

Which plot shows a cumulative histogram of data sampled from a normal distribution?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

data = np.random.normal(0, 1, 1000)
plt.figure(figsize=(8,4))
plt.subplot(1,2,1)
plt.hist(data, bins=30)
plt.title('Regular Histogram')
plt.subplot(1,2,2)
plt.hist(data, bins=30, cumulative=True)
plt.title('Cumulative Histogram')
plt.tight_layout()
plt.show()

A The right plot with bars increasing and never decreasing

B Neither plot is a histogram

C Both plots show cumulative histograms

D The left plot with bars showing frequency counts

💡 Hint

Cumulative histograms always increase or stay the same as bins increase.

The right plot uses cumulative=True, so the bars accumulate counts and never decrease, showing a cumulative histogram.

🧠 Conceptual

advanced

Effect of cumulative=True on histogram counts

What happens to the counts array when you set cumulative=True in plt.hist compared to cumulative=False?

A Counts become negative for bins with no data

B Counts show total data points up to each bin edge, increasing or staying the same

C Counts show only the data points in each bin, independent of previous bins

D Counts are normalized to sum to 1

💡 Hint

Cumulative means adding up counts as you move through bins.

With cumulative=True, counts accumulate data points from all previous bins, so counts never decrease.

🔧 Debug

expert

Identify the error in cumulative histogram code

What error does this code raise? import matplotlib.pyplot as plt plt.hist([1,2,3,4,5], bins=3, cumulative='yes')

Matplotlib

import matplotlib.pyplot as plt

plt.hist([1,2,3,4,5], bins=3, cumulative='yes')

A TypeError: cumulative must be a boolean, not str

B ValueError: bins must be an integer or sequence

C SyntaxError: invalid syntax

D No error, runs successfully

💡 Hint

Check the type expected for the cumulative parameter.

The cumulative parameter expects a boolean True or False, not a string. Passing 'yes' causes a TypeError.