np.zeros() for zero-filled arrays in NumPy - Mini Project: Build & Apply

Create and Use Zero-Filled Arrays with np.zeros()

📖 Scenario: You are working as a data analyst. Sometimes you need to create empty tables of numbers to fill later. These tables start with all zeros.

🎯 Goal: Learn how to create zero-filled arrays using np.zeros() and print the result.

📋 What You'll Learn

Create a zero-filled array with exact shape

Use a variable to store the shape

Use np.zeros() with the shape variable

Print the zero-filled array

💡 Why This Matters

🌍 Real World

Zero-filled arrays are useful when you need a blank table or matrix to fill with data later, such as in image processing or initializing weights in machine learning.

💼 Career

Data scientists and analysts often create zero arrays as starting points for calculations, simulations, or data storage.

1

Create a shape variable for the array

Create a variable called shape and set it to the tuple (3, 4) to represent 3 rows and 4 columns.

NumPy

# Create a variable called shape with value (3, 4)
# Your code here

Hint

Use parentheses to create a tuple like (3, 4).

2

Import numpy and create a zero-filled array

Import the numpy library as np. Then create a variable called zero_array using np.zeros() with the shape variable.

NumPy

shape = (3, 4)
# Import numpy as np and create zero_array with np.zeros(shape)
# Your code here

Hint

Use import numpy as np to import numpy.

Use np.zeros(shape) to create the array.

3

Check the shape of the zero-filled array

Use print() to display the shape of zero_array by accessing its shape attribute.

NumPy

import numpy as np
shape = (3, 4)
zero_array = np.zeros(shape)
# Print the shape of zero_array
# Your code here

Hint

Use zero_array.shape to get the shape tuple.

4

Print the zero-filled array

Use print() to display the entire zero_array.

NumPy

import numpy as np
shape = (3, 4)
zero_array = np.zeros(shape)
print(zero_array.shape)
# Print the zero_array
# Your code here

Hint

Just use print(zero_array) to see all zeros.

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'