np.round(), np.floor(), np.ceil() in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.round() with decimals parameter

What is the output of this code snippet?

NumPy

import numpy as np
arr = np.array([1.234, 2.345, 3.456])
result = np.round(arr, decimals=1)
print(result)

A [1.23 2.35 3.46]

B [2.0 2.0 3.0]

C [1.0 2.0 3.0]

D [1.2 2.3 3.5]

💡 Hint

np.round rounds each element to the specified number of decimal places.

np.round with decimals=1 rounds each number to one decimal place, so 1.234 becomes 1.2, 2.345 becomes 2.3, and 3.456 becomes 3.5.

❓ Predict Output

intermediate

Output of np.floor() on negative and positive values

What is the output of this code?

NumPy

import numpy as np
arr = np.array([-1.7, -0.2, 0.2, 1.7])
result = np.floor(arr)
print(result)

A [-1. -0. 0. 1.]

B [-2. -1. 0. 1.]

C [-1. -1. 0. 1.]

D [-2. -1. 1. 2.]

💡 Hint

np.floor returns the largest integer less than or equal to each element.

For negative numbers, floor goes to the next lower integer: floor(-1.7) is -2, floor(-0.2) is -1. For positive numbers, floor truncates decimals: floor(0.2) is 0, floor(1.7) is 1.

❓ Predict Output

advanced

Output of np.ceil() with mixed values

What does this code print?

NumPy

import numpy as np
arr = np.array([1.1, 2.5, 3.0, -1.1, -2.5])
result = np.ceil(arr)
print(result)

A [ 2. 3. 3. -1. -3.]

B [ 1. 3. 3. -2. -3.]

C [ 1. 2. 3. -1. -2.]

D [ 2. 3. 3. -1. -2.]

💡 Hint

np.ceil returns the smallest integer greater than or equal to each element.

np.ceil returns the smallest integer greater than or equal to each element (towards +∞). 1.1→2, 2.5→3, 3.0→3, -1.1→-1, -2.5→-2.

❓ Predict Output

advanced

Number of elements after rounding and filtering

How many elements are in the array after rounding to 0 decimals and filtering values > 2?

NumPy

import numpy as np
arr = np.array([1.9, 2.1, 2.5, 3.4, 1.2])
rounded = np.round(arr, decimals=0)
filtered = rounded[rounded > 2]
print(len(filtered))

A 4

B 2

C 1

D 3

💡 Hint

Round first, then count how many are greater than 2.

Rounded array is [2., 2., 2., 3., 1.]. Values > 2 are only 3., so count is 1.

🧠 Conceptual

expert

Understanding behavior of np.round() with negative decimals

What is the output of this code snippet?

NumPy

import numpy as np
arr = np.array([123.45, 678.91, 234.56])
result = np.round(arr, decimals=-1)
print(result)

A [120. 680. 230.]

B [123. 679. 235.]

C [100. 600. 200.]

D [130. 680. 240.]

💡 Hint

Negative decimals rounds to the left of the decimal point.

Rounding with decimals=-1 rounds to the nearest 10: 123.45 to 120, 678.91 to 680, 234.56 to 230.