np.round(), np.floor(), np.ceil() in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to round the values in the array to the nearest integer.

NumPy

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

Drag options to blanks, or click blank then click option'

Aceil

Bround

Cfloor

Dabs

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.floor or np.ceil instead of np.round

Forgetting to import numpy

The np.round() function rounds each element in the array to the nearest integer.

2fill in blank

medium

Complete the code to get the largest integer less than or equal to each element in the array.

NumPy

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

Drag options to blanks, or click blank then click option'

Aabs

Bround

Cceil

Dfloor

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.ceil instead of np.floor

Confusing floor with round

The np.floor() function returns the largest integer less than or equal to each element.

3fill in blank

hard

Fix the error in the code to get the smallest integer greater than or equal to each element.

NumPy

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

Drag options to blanks, or click blank then click option'

Afloor

Babs

Cceil

Dround

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.floor instead of np.ceil

Using np.round instead of np.ceil

The np.ceil() function returns the smallest integer greater than or equal to each element.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths rounded down if length is greater than 3.

NumPy

import numpy as np
words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: np.[1](len(word)) for word in words if len(word) [2] 3}
print(lengths)

Drag options to blanks, or click blank then click option'

Afloor

B>

C<=

Dround

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.round instead of np.floor

Using <= instead of > in the condition

We use np.floor to round lengths down and filter words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths rounded up if length is less than 5.

NumPy

import numpy as np
words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word.[1](): np.[2](len(word)) for word in words if len(word) [3] 5}
print(lengths)

Drag options to blanks, or click blank then click option'

Aupper

Bceil

C<

Dfloor

Attempts:

3 left

💡 Hint

Common Mistakes

Using floor instead of ceil for rounding

Using > instead of < in the condition

Forgetting to convert words to uppercase

We convert words to uppercase with upper(), round lengths up with ceil, and filter words with length less than 5 using <.

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