Percentiles with np.percentile() in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.percentile() on a simple array

What is the output of this code snippet?

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
result = np.percentile(arr, 40)
print(result)

A 26.0

B 20.0

C 30.0

D 40.0

💡 Hint

Percentile 40 means the value below which 40% of data falls.

The 40th percentile is calculated by linear interpolation between 20 and 30, resulting in 26.0.

❓ data_output

intermediate

Percentiles of a 2D array along axis 0

What is the output of np.percentile(arr, 50, axis=0) for the given 2D array?

NumPy

import numpy as np
arr = np.array([[1, 3, 5], [2, 4, 6], [3, 5, 7]])
result = np.percentile(arr, 50, axis=0)
print(result)

A [3. 5. 7.]

B [1. 3. 5.]

C [2. 4. 6.]

D [2.5 4.5 6.5]

💡 Hint

50th percentile is the median along the specified axis.

The median along axis 0 is the middle value of each column: [2, 4, 6].

❓ visualization

advanced

Visualizing percentiles on a dataset

Which option correctly describes the plot generated by this code?

NumPy

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(0)
data = np.random.normal(0, 1, 1000)
percentiles = np.percentile(data, [25, 50, 75])
plt.hist(data, bins=30, alpha=0.5)
for p in percentiles:
    plt.axvline(p, color='r', linestyle='--')
plt.show()

A Histogram with red dashed lines at the minimum, median, and maximum values

B Scatter plot of data points with red dashed lines at quartiles

C Line plot of data with red dashed lines at mean and standard deviation

D Histogram with red dashed lines at the 25th, 50th, and 75th percentiles

💡 Hint

Percentiles 25, 50, and 75 correspond to quartiles.

The code plots a histogram and draws vertical red dashed lines at the 25th, 50th (median), and 75th percentiles.

🧠 Conceptual

advanced

Understanding interpolation in np.percentile()

If np.percentile() is called with interpolation='nearest' on the array [1, 2, 3, 4], what is the 30th percentile value?

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4])
result = np.percentile(arr, 30, interpolation='nearest')
print(result)

A 1

B 2

C 4

D 3

💡 Hint

Nearest interpolation picks the closest data point to the percentile rank.

The 30th percentile rank corresponds closest to the second element (value 2) when using nearest interpolation.

🔧 Debug

expert

Error raised by incorrect np.percentile() usage

What error does this code raise?

NumPy

import numpy as np
arr = np.array([1, 2, 3])
result = np.percentile(arr, 110)
print(result)

A ValueError: percentile must be in the range [0, 100]

B IndexError: index out of bounds

C No error, returns 3

D TypeError: unsupported operand type(s)

💡 Hint

Percentiles must be between 0 and 100 inclusive.

Percentile values outside 0-100 range cause a ValueError in np.percentile().