np.zeros() for zero-filled arrays in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.zeros with shape and dtype

What is the output of this code snippet?

import numpy as np
arr = np.zeros((2, 3), dtype=int)
print(arr)

NumPy

import numpy as np
arr = np.zeros((2, 3), dtype=int)
print(arr)

A

[[0. 0. 0.]
 [0. 0. 0.]]

B

[[0 0 0]
 [0 0 0]]

C

[[0 0 0 0]
 [0 0 0 0]]

D [0 0 0 0 0 0]

💡 Hint

Check the shape and data type specified in np.zeros.

np.zeros creates an array of zeros with the given shape and data type. Here, shape is (2,3) and dtype is int, so the output is a 2x3 array of integer zeros.

❓ data_output

intermediate

Number of elements in np.zeros array

How many elements are in the array created by this code?

import numpy as np
arr = np.zeros((4, 5))
print(arr.size)

NumPy

import numpy as np
arr = np.zeros((4, 5))
print(arr.size)

A 20

B 9

C 10

D 5

💡 Hint

Multiply the dimensions of the shape to find total elements.

The shape (4,5) means 4 rows and 5 columns, so total elements = 4 * 5 = 20.

🔧 Debug

advanced

Identify the error in np.zeros usage

What error does this code produce?

import numpy as np
arr = np.zeros(3, 4)
print(arr)

NumPy

import numpy as np
arr = np.zeros(3, 4)
print(arr)

A TypeError: data type not understood

B TypeError: 'int' object is not iterable

C TypeError: zeros() missing 1 required positional argument: 'dtype'

D TypeError: zeros() takes 1 positional argument but 2 were given

💡 Hint

Check the function signature of np.zeros.

np.zeros expects the first argument to be the shape as a single tuple or int. Passing two separate ints causes a TypeError about argument count.

🚀 Application

advanced

Create a 3D zero-filled array and check shape

Which option creates a 3D zero-filled array with shape (2, 3, 4) and prints its shape correctly?

A

arr = np.zeros([2, 3, 4])
print(arr.shape)

B

arr = np.zeros(2, 3, 4)
print(arr.shape)

C

arr = np.zeros((2, 3, 4))
print(arr.shape)

D

arr = np.zeros({2, 3, 4})
print(arr.shape)

💡 Hint

np.zeros expects shape as a tuple or list as first argument.

Option C correctly passes a tuple as shape. Option C uses a list which also works but is less common. Option C passes multiple arguments causing error. Option C uses a set which is unordered and invalid.

🧠 Conceptual

expert

Memory size of np.zeros array

Given this code:

import numpy as np
arr = np.zeros((1000, 1000), dtype=np.float64)
print(arr.nbytes)

What is the output value printed?

NumPy

import numpy as np
arr = np.zeros((1000, 1000), dtype=np.float64)
print(arr.nbytes)

A 8000000

B 4000000

C 1000000

D 16000000

💡 Hint

Each float64 uses 8 bytes. Multiply by total elements.

The array has 1,000,000 elements (1000*1000). Each float64 uses 8 bytes. Total bytes = 1,000,000 * 8 = 8,000,000 bytes.

Practice

1. What does the np.zeros() function do in NumPy?

easy

A. Creates an array filled with zeros

B. Creates an array filled with ones

C. Creates an array with random values

D. Creates an empty array with no elements

Solution

1. Step 1: Understand the purpose of np.zeros()

   This function is designed to create arrays where every element is zero.

2. Step 2: Compare with other array creation functions

   Unlike np.ones() or random array functions, np.zeros() specifically fills the array with zeros.

3. Final Answer:

   Creates an array filled with zeros -> Option A

4. Quick Check:

   np.zeros() = zero-filled array [OK]

Hint: Remember zeros means all elements are zero [OK]

Common Mistakes:

• Confusing with np.ones()
• Thinking it creates empty arrays
• Assuming it creates random values

2. Which of the following is the correct syntax to create a 3x3 zero-filled array using NumPy?

easy

A. np.zeros(3,3)

B. np.zeros[3,3]

C. np.zeros((3,3))

D. np.zeros{3,3}

Solution

1. Step 1: Check the shape argument format

   The shape must be passed as a tuple, so it should be (3,3).

2. Step 2: Validate the function call syntax

   Only parentheses () are valid for function calls, so np.zeros((3,3)) is correct.

3. Final Answer:

   np.zeros((3,3)) -> Option C

4. Quick Check:

   Shape as tuple inside parentheses [OK]

Hint: Use double parentheses for shape tuple [OK]

Common Mistakes:

• Using commas without tuple
• Using square or curly brackets
• Missing parentheses

3. What is the output of the following code?

import numpy as np
arr = np.zeros(4, dtype=int)
print(arr)

medium

A. [0 0 0 0]

B. [0. 0. 0. 0.]

C. [1 1 1 1]

D. [False False False False]

Solution

1. Step 1: Understand np.zeros(4, dtype=int)

   This creates a 1D array of length 4 filled with zeros, with integer type.

2. Step 2: Check the printed output format

   Since dtype is int, zeros are printed as integers without decimal points.

3. Final Answer:

   [0 0 0 0] -> Option A

4. Quick Check:

   Integer zeros printed without decimals [OK]

Hint: dtype=int means zeros print as integers [OK]

Common Mistakes:

• Expecting float zeros with decimals
• Confusing with ones array
• Thinking output is boolean

4. Identify the error in this code snippet:

import numpy as np
arr = np.zeros[5]
print(arr)

medium

A. Missing dtype argument

B. Using square brackets instead of parentheses for function call

C. Shape argument should be a tuple

D. np.zeros cannot create 1D arrays

Solution

1. Step 1: Check function call syntax

   Functions in Python require parentheses (), not square brackets [].

2. Step 2: Confirm correct usage of np.zeros

   The shape argument can be an integer for 1D arrays, so 5 is valid.

3. Final Answer:

   Using square brackets instead of parentheses for function call -> Option B

4. Quick Check:

   Function calls need parentheses [OK]

Hint: Use () for functions, not [] [OK]

Common Mistakes:

• Using [] instead of ()
• Thinking dtype is mandatory
• Confusing shape tuple for 1D arrays

5. You want to create a zero-filled 2D array with 3 rows and 4 columns, but the array must store boolean values. Which code is correct?

hard

A. np.zeros((3,4), type=bool)

B. np.zeros(3,4, dtype=bool)

C. np.zeros([3,4], dtype=bool)

D. np.zeros((3,4), dtype=bool)

Solution

1. Step 1: Check shape argument format

   The shape must be a tuple, so (3,4) is correct.

2. Step 2: Verify dtype argument name and value

   The correct keyword is dtype, and bool is valid to create boolean arrays.

3. Step 3: Eliminate incorrect options

   Using the wrong keyword type instead of dtype, passing shape as separate arguments like np.zeros(3,4, dtype=bool) without tuple parentheses, using a list [3,4] instead of tuple.

4. Final Answer:

   np.zeros((3,4), dtype=bool) -> Option D

5. Quick Check:

   Shape tuple and dtype=bool required [OK]

Hint: Use tuple for shape and dtype=bool for boolean zeros [OK]

Common Mistakes:

• Passing shape as separate args
• Using list instead of tuple
• Wrong keyword 'type' instead of 'dtype'