np.round(), np.floor(), np.ceil() in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does np.round() do in numpy?

np.round() rounds each number in an array to the nearest integer or to a specified number of decimal places.

beginner

Explain the function of np.floor().

np.floor() takes each number in an array and rounds it down to the nearest whole number (integer) less than or equal to the number.

beginner

What does np.ceil() do?

np.ceil() rounds each number in an array up to the nearest whole number (integer) greater than or equal to the number.

intermediate

How does np.round() differ from np.floor() and np.ceil()?

np.round() rounds to the nearest integer (up or down), while np.floor() always rounds down and np.ceil() always rounds up.

beginner

If you have the number 3.7, what will np.round(), np.floor(), and np.ceil() return?

np.round(3.7) returns 4.0<br>np.floor(3.7) returns 3.0<br>np.ceil(3.7) returns 4.0

What does np.floor(2.9) return?

A 2.9

B 3.0

C 2.0

D 3.9

np.floor() rounds down to the nearest integer, so 2.9 becomes 2.0.

Which function rounds numbers to the nearest integer, either up or down?

A np.round()

B np.floor()

C np.ceil()

D None of these

np.round() rounds to the nearest integer, up or down depending on the decimal.

What will np.ceil(-1.2) return?

A -2.0

B -0.0

C -1.2

D -1.0

np.ceil() rounds up to the nearest integer. For negative numbers, 'up' means closer to zero, so -1.2 becomes -1.0.

How can you round numbers in a numpy array to 2 decimal places?

A np.round(array, 2)

B np.floor(array, 2)

C np.ceil(array, 2)

D np.round(array)

Use np.round() with the second argument as the number of decimals, like 2.

Which function always rounds numbers up?

A np.floor()

B np.ceil()

C np.round()

D np.trunc()

np.ceil() always rounds numbers up to the nearest integer.

Describe the difference between np.round(), np.floor(), and np.ceil() with examples.

Think about how each function treats decimals differently.

Explain how you would round all numbers in a numpy array to 1 decimal place using numpy functions.

Look for a function that allows decimal precision.