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.

Practice

1. What does the function np.floor() do to a decimal number?

easy

A. Rounds the number down to the nearest whole number

B. Rounds the number up to the nearest whole number

C. Rounds the number to the nearest integer based on decimals

D. Leaves the number unchanged

Solution

1. Step 1: Understand the behavior of np.floor()

   It always rounds any decimal number down to the nearest whole number, regardless of the decimal part.

2. Step 2: Compare with other rounding functions

   Unlike np.ceil() which rounds up, np.floor() always rounds down.

3. Final Answer:

   Rounds the number down to the nearest whole number -> Option A

4. Quick Check:

   np.floor(3.7) = 3 [OK]

Hint: Floor always rounds down, no matter the decimal [OK]

Common Mistakes:

• Confusing floor with ceil
• Thinking floor rounds to nearest integer
• Assuming floor changes only if decimal > 0.5

2. Which of the following is the correct syntax to round the array arr = np.array([1.2, 2.5, 3.7]) to 1 decimal place using np.round()?

easy

A. np.round(arr, decimals=0.1)

B. np.round(arr, decimals=1)

C. np.round(arr, 0)

D. np.round(arr, places=1)

Solution

1. Step 1: Check np.round() parameter for decimals

   The parameter to specify decimal places is named 'decimals' and expects an integer.

2. Step 2: Validate each option

   A: decimals=0.1 invalid (must be integer). B: np.round(arr, 0) rounds to 0 decimal places. C: np.round(arr, decimals=1) correct. D: 'places' not a valid parameter.

3. Final Answer:

   np.round(arr, decimals=1) -> Option B

4. Quick Check:

   np.round(arr, decimals=1) rounds to 1 decimal [OK]

Hint: Use decimals=number to set decimal places in np.round() [OK]

Common Mistakes:

• Using wrong parameter name like 'places'
• Passing float instead of int for decimals
• Omitting decimals parameter and expecting decimal rounding

3. What is the output of the following code?

import numpy as np
arr = np.array([1.7, 2.3, 3.5])
result = np.ceil(arr)
print(result)

medium

A. [2. 3. 4.]

B. [2. 2. 3.]

C. [1. 3. 4.]

D. [1. 2. 3.]

Solution

1. Step 1: Understand np.ceil() behavior on each element

   np.ceil() rounds each number up to the nearest whole number: 1.7 -> 2, 2.3 -> 3, 3.5 -> 4.

2. Step 2: Apply np.ceil() to the array

   The resulting array is [2., 3., 4.].

3. Final Answer:

   [2. 3. 4.] -> Option A

4. Quick Check:

   np.ceil rounds decimals up [OK]

Hint: Ceil always rounds decimals up to next integer [OK]

Common Mistakes:

• Confusing ceil with floor
• Expecting rounding to nearest integer
• Ignoring decimal part in output

4. The following code throws an error. What is the mistake?

import numpy as np
arr = np.array([1.2, 2.5, 3.7])
result = np.round(arr, decimal=1)
print(result)

medium

A. np.round() requires the second argument to be a string

B. np.round() cannot round arrays

C. The array must be integers to use np.round()

D. The parameter name should be 'decimals' not 'decimal'

Solution

1. Step 1: Identify the parameter name error

   The correct parameter name for decimal places in np.round() is 'decimals', not 'decimal'.

2. Step 2: Confirm np.round() usage

   np.round() works on numpy arrays and accepts an integer for decimals parameter.

3. Final Answer:

   The parameter name should be 'decimals' not 'decimal' -> Option D

4. Quick Check:

   Use decimals=1, not decimal=1 [OK]

Hint: Remember parameter is 'decimals', plural, in np.round() [OK]

Common Mistakes:

• Using 'decimal' instead of 'decimals'
• Thinking np.round() only works on scalars
• Passing string instead of integer for decimals

5. You have the array arr = np.array([1.25, 2.75, 3.5, 4.1]). You want to round each number to the nearest integer but always round .5 up. Which combination of numpy functions will achieve this?

hard

A. Use np.round(arr)

B. Use np.ceil(arr - 0.5)

C. Use np.floor(arr + 0.5)

D. Use np.round(arr, decimals=0)

Solution

1. Step 1: Understand rounding .5 up behavior

   Standard np.round() rounds .5 to nearest even integer, not always up.

2. Step 2: Use floor with offset to force .5 up rounding

   Adding 0.5 then applying np.floor() rounds numbers so that .5 always rounds up.

3. Step 3: Check example

   1.25 + 0.5 = 1.75 floor = 1, 2.75 + 0.5 = 3.25 floor = 3, 3.5 + 0.5 = 4.0 floor = 4, 4.1 + 0.5 = 4.6 floor = 4.

4. Final Answer:

   Use np.floor(arr + 0.5) -> Option C

5. Quick Check:

   Floor after adding 0.5 rounds .5 up [OK]

Hint: Add 0.5 then floor to always round .5 up [OK]

Common Mistakes:

• Using np.round() which rounds .5 to nearest even
• Using ceil incorrectly with subtraction
• Ignoring .5 rounding behavior