np.round(), np.floor(), np.ceil() in NumPy - Mini Project: Build & Apply

Using np.round(), np.floor(), and np.ceil() with NumPy Arrays

📖 Scenario: Imagine you work at a weather station. You have temperature readings with decimals, but you need to prepare reports with rounded, floored, and ceiled values for different uses.

🎯 Goal: You will create a NumPy array of temperature readings, then use np.round(), np.floor(), and np.ceil() to transform these readings for reporting.

📋 What You'll Learn

Create a NumPy array called temps with exact values: 23.7, 18.2, 30.9, 15.5, 21.3

Create a variable called decimals and set it to 0

Use np.round() with temps and decimals to create rounded_temps

Use np.floor() with temps to create floored_temps

Use np.ceil() with temps to create ceiled_temps

Print rounded_temps, floored_temps, and ceiled_temps each on a separate line

💡 Why This Matters

🌍 Real World

Weather stations and many scientific fields often need to round measurements for reports or analysis. Knowing how to round numbers up, down, or to the nearest value helps prepare data correctly.

💼 Career

Data scientists and analysts frequently clean and prepare data using rounding functions to simplify numbers or meet reporting standards.

1

Create the temperature array

Import NumPy as np and create a NumPy array called temps with these exact values: 23.7, 18.2, 30.9, 15.5, 21.3

NumPy

import numpy as np
# Create the NumPy array temps with the given values
# Your code here

Hint

Use np.array() to create the array with the exact numbers inside square brackets.

2

Set the decimals variable

Create a variable called decimals and set it to 0 to specify rounding to whole numbers

NumPy

import numpy as np
temps = np.array([23.7, 18.2, 30.9, 15.5, 21.3])
# Create the decimals variable and set it to 0
# Your code here

Hint

Just assign 0 to the variable decimals.

3

Apply rounding, flooring, and ceiling

Use np.round() with temps and decimals to create rounded_temps. Use np.floor() with temps to create floored_temps. Use np.ceil() with temps to create ceiled_temps

NumPy

import numpy as np
temps = np.array([23.7, 18.2, 30.9, 15.5, 21.3])
decimals = 0
# Create rounded_temps using np.round with temps and decimals
# Create floored_temps using np.floor with temps
# Create ceiled_temps using np.ceil with temps
# Your code here

Hint

Use the three NumPy functions exactly as shown with the correct variables.

4

Print the results

Print rounded_temps, floored_temps, and ceiled_temps each on its own line

NumPy

import numpy as np
temps = np.array([23.7, 18.2, 30.9, 15.5, 21.3])
decimals = 0
rounded_temps = np.round(temps, decimals)
floored_temps = np.floor(temps)
ceiled_temps = np.ceil(temps)
# Print rounded_temps
# Print floored_temps
# Print ceiled_temps
# Your code here

Hint

Use three print() statements, one for each array.

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