np.empty() for uninitialized arrays in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an uninitialized NumPy array of shape (3, 3).

NumPy

import numpy as np
arr = np.[1]((3, 3))
print(arr)

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

Azeros

Bempty

Cones

Darray

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.zeros() or np.ones() instead of np.empty()

Trying to pass shape as separate arguments instead of a tuple

The np.empty() function creates an uninitialized array of the given shape. It does not set values to zero or one.

2fill in blank

medium

Complete the code to create an uninitialized array of integers with shape (2, 4).

NumPy

import numpy as np
arr = np.empty((2, 4), dtype=[1])
print(arr)

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

Aint

Bfloat

Cstr

Dbool

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'float' as dtype when integers are needed

Passing dtype as a string instead of a type

Setting dtype=int creates an array of integers. The np.empty() function does not initialize values.

3fill in blank

hard

Fix the error in the code to create an uninitialized array of shape (5,).

NumPy

import numpy as np
arr = np.empty([1])
print(arr)

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

A(5,)

B[5]

C5

D{5}

Attempts:

3 left

💡 Hint

Common Mistakes

Passing an integer instead of a tuple as shape

Using square brackets instead of parentheses for shape

The shape argument must be a tuple. For a 1D array of length 5, use (5,).

4fill in blank

hard

Fill both blanks to create an uninitialized 2D array of floats with shape (3, 2).

NumPy

import numpy as np
arr = np.[1]([2], dtype=float)
print(arr)

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

Aempty

B(3, 2)

C[3, 2]

Dzeros

Attempts:

3 left

💡 Hint

Common Mistakes

Using zeros instead of empty

Passing shape as a list instead of a tuple

Use np.empty with a tuple shape (3, 2) to create an uninitialized 2D float array.

5fill in blank

hard

Fill all three blanks to create an uninitialized array with shape (4, 4), integer type, and print its shape.

NumPy

import numpy as np
arr = np.[1]([2], dtype=[3])
print(arr.shape)

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

Aempty

B(4, 4)

Cint

Dfloat

Attempts:

3 left

💡 Hint

Common Mistakes

Using float dtype instead of int

Passing shape as a list instead of a tuple

Use np.empty with shape (4, 4) and dtype=int to create the array. Printing arr.shape shows the array's dimensions.

Practice

1. What does np.empty() do when creating a new array?

easy

A. Creates an array without initializing its values

B. Creates an array filled with zeros

C. Creates an array filled with ones

D. Creates an array filled with random numbers

Solution

1. Step 1: Understand np.empty() purpose

   np.empty() allocates memory for an array but does not set values, so the content is uninitialized.

2. Step 2: Compare with other functions

   Functions like np.zeros() or np.ones() initialize values, but np.empty() does not.

3. Final Answer:

   Creates an array without initializing its values -> Option A

4. Quick Check:

   np.empty() = uninitialized array [OK]

Hint: Remember: empty means no initial values set [OK]

Common Mistakes:

• Thinking np.empty() fills with zeros
• Confusing np.empty() with np.random
• Assuming np.empty() initializes with ones

2. Which of the following is the correct syntax to create an uninitialized 2x3 array using np.empty()?

easy

A. np.empty((2, 3))

B. np.empty(2, 3)

C. np.empty((3, 2))

D. np.empty{2, 3}

Solution

1. Step 1: Check correct argument type for shape

   np.empty() expects a single tuple for shape, so (2, 3) is correct.

2. Step 2: Identify correct syntax

   np.empty((2, 3)) uses np.empty((2, 3)), which is valid. np.empty((3, 2)) uses swapped dimensions and creates 3x2 array instead of 2x3. np.empty(2, 3) passes two arguments incorrectly. np.empty{2, 3} uses braces which is invalid syntax.

3. Final Answer:

   np.empty((2, 3)) -> Option A

4. Quick Check:

   Shape must be tuple in np.empty() [OK]

Hint: Use tuple (rows, cols) inside np.empty() [OK]

Common Mistakes:

• Passing multiple arguments instead of a tuple
• Using curly braces instead of parentheses
• Swapping dimensions to (3, 2)

3. What will be the output of this code?

import numpy as np
arr = np.empty((2,2))
print(arr)

medium

A. SyntaxError

B. [[1. 1.]
[1. 1.]]

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

D. An array with random uninitialized values

Solution

1. Step 1: Understand np.empty() output

   np.empty() creates an array without initializing values, so the content is random garbage data from memory.

2. Step 2: Predict printed output

   The printed array will show unpredictable float numbers, not zeros or ones.

3. Final Answer:

   An array with random uninitialized values -> Option D

4. Quick Check:

   np.empty() output = random uninitialized values [OK]

Hint: np.empty() shows random values, not zeros or ones [OK]

Common Mistakes:

• Expecting zeros or ones in output
• Thinking np.empty() initializes values
• Confusing with np.zeros() or np.ones()

4. Identify the error in this code snippet:

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

medium

A. np.empty() does not accept integers

B. Shape argument must be a single tuple, not two separate arguments

C. Missing import statement

D. print() cannot print numpy arrays

Solution

1. Step 1: Check np.empty() argument format

   np.empty() expects one argument for shape, which should be a tuple like (3, 4).

2. Step 2: Identify error in code

   The code passes two separate arguments 3, 4 instead of a tuple, causing a TypeError.

3. Final Answer:

   Shape argument must be a single tuple, not two separate arguments -> Option B

4. Quick Check:

   Shape must be tuple in np.empty() [OK]

Hint: Pass shape as one tuple, e.g. (3,4) [OK]

Common Mistakes:

• Passing multiple integers instead of a tuple
• Forgetting to import numpy
• Thinking print() can't show arrays

5. You want to create a large array quickly and fill it later. Which is the best way to do this using np.empty()?

import numpy as np
arr = np.empty((1000, 1000))
# Next step: fill arr with values

Why is np.empty() preferred here over np.zeros()?

hard

A. Because np.empty() creates a copy of an existing array

B. Because np.empty() fills with zeros automatically

C. Because np.empty() is faster as it skips initialization

D. Because np.empty() initializes with random values

Solution

1. Step 1: Understand performance difference

   np.empty() allocates memory without setting values, so it is faster than np.zeros() which sets all values to zero.

2. Step 2: Reason why this is useful

   When you plan to fill the array later, skipping initialization saves time and resources.

3. Final Answer:

   Because np.empty() is faster as it skips initialization -> Option C

4. Quick Check:

   np.empty() = fast allocation without init [OK]

Hint: Use np.empty() for speed when filling later [OK]

Common Mistakes:

• Thinking np.empty() initializes with zeros
• Confusing np.empty() with np.copy()
• Assuming np.empty() fills with random values intentionally