Histogram computation with np.histogram() in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.histogram() with bins=6

What is the output of the following code snippet?

NumPy

import numpy as np

arr = np.array([1, 2, 2, 3, 4, 5, 5, 5, 6])
hist, bins = np.histogram(arr, bins=6)
print(hist, bins)

A [1 2 1 0 3 2] [1. 2. 3. 4. 5. 6. ]

B [1 2 1 1 3 1] [1. 2. 3. 4. 5. 6. 7. ]

C [1 2 1 1 3 2] [1. 1.83333333 2.66666667 3.5 4.33333333 5.16666667 6. ]

D [1 2 1 1 3 2] [1. 2. 3. 4. 5. 6. 7. ]

💡 Hint

Check how np.histogram divides the range into equal-width bins when bins=6.

np.histogram with bins=6 creates 6 bins between min and max values. Here, the bins are automatically calculated with equal width between 1 and 6, resulting in 6 bins with counts as shown.

❓ data_output

intermediate

Number of bins and counts with custom bins

Given the array and bins, what is the output counts array from np.histogram?

NumPy

import numpy as np

arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
bins = [0, 3, 6, 9]
hist, _ = np.histogram(arr, bins=bins)
print(hist)

A [3 4 3]

B [3 3 4]

C [4 3 3]

D [3 3 3]

💡 Hint

Count how many numbers fall into each bin range: [0-3), [3-6), [6-9).

The bins are [0,3), [3,6), [6,9). Values 0,1,2 fall in first bin (3 items), 3,4,5 in second (3 items), 6,7,8 in third (3 items). The value 9 is excluded as bins are half-open intervals.

🔧 Debug

advanced

Identify the error in np.histogram bin specification

What error does the following code raise?

NumPy

import numpy as np

arr = np.array([1, 2, 3, 4, 5])
bins = [5, 4, 3, 2, 1]
hist, edges = np.histogram(arr, bins=bins)

A ValueError: bins must increase monotonically.

B TypeError: bins must be an integer or sequence.

C IndexError: list index out of range.

D No error, runs successfully.

💡 Hint

Bins must be sorted in ascending order.

np.histogram requires bins to be monotonically increasing. Here bins are in descending order, so it raises a ValueError.

❓ visualization

advanced

Histogram bin edges with uneven bin widths

What are the bin edges and counts for this histogram?

NumPy

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
bins = [1, 3, 6, 10]
hist, edges = np.histogram(arr, bins=bins)
print(hist, edges)

A [2 3 4] [ 1 3 6 10]

B [2 4 3] [ 1 3 6 10]

C [3 3 3] [ 1 3 6 10]

D [2 3 3] [ 1 3 6 10]

💡 Hint

Count how many values fall into each bin: [1-3), [3-6), [6-10).

Values 1 and 2 fall in first bin (2 items), 3,4,5 in second (3 items), 6,7,8,9 in third (4 items).

🚀 Application

expert

Calculate histogram and cumulative counts

Given the array, which option correctly computes the histogram counts and cumulative counts using np.histogram?

NumPy

import numpy as np

arr = np.array([2, 4, 4, 4, 5, 5, 7, 9])
bins = [0, 3, 6, 9, 12]
hist, edges = np.histogram(arr, bins=bins)
cum_counts = np.cumsum(hist)
print(hist, cum_counts)

A [1 4 2 1] [1 5 7 8]

B [1 5 1 1] [1 6 7 8]

C [2 4 1 1] [2 6 7 8]

D [1 5 2 0] [1 6 8 8]

💡 Hint

Count values in each bin and then sum counts cumulatively.

Bins: [0-3), [3-6), [6-9), [9-12). Values: 2 in first bin (1 item), 4,4,4,5,5 in second (5 items), 7 in third (1 item), 9 in fourth (1 item). Cumulative sums add counts progressively.