Array attributes (shape, dtype, ndim, size) in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to print the number of dimensions of the array.

NumPy

import numpy as np
arr = np.array([[1, 2], [3, 4]])
print(arr.[1])

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

Andim

Bshape

Csize

Ddtype

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'shape' instead of 'ndim' to get the number of dimensions.

Using 'size' which gives total elements, not dimensions.

The ndim attribute tells how many dimensions the array has.

2fill in blank

medium

Complete the code to print the total number of elements in the array.

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print(arr.[1])

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

Asize

Bshape

Cndim

Ddtype

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'shape' which returns a tuple, not a single number.

Using 'ndim' which returns number of dimensions, not elements.

The size attribute gives the total number of elements in the array.

3fill in blank

medium

Complete the code to print the data type of the array elements.

NumPy

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

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

Ashape

Bdtype

Csize

Dndim

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'shape' or 'size' instead of 'dtype'.

Using 'ndim' which returns number of dimensions.

The dtype attribute gives the data type of the array elements.

4fill in blank

hard

Fill both blanks to print the number of rows and columns of the array.

NumPy

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr.[1][0], arr.[2][1])

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

Andim

Bshape

Csize

Ddtype

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ndim' which returns a single number, not indexable.

Using 'size' which is total elements, not dimensions.

The shape attribute returns a tuple of the array dimensions. shape[0] is the number of rows, shape[1] is the number of columns.

5fill in blank

hard

Fill all three blanks to compute the total number of elements by multiplying the dimensions.

NumPy

import numpy as np
arr = np.zeros((2, 3, 4))
print(arr.[1][0] * arr.[2][1] * arr.[3][2])

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

Andim

Bshape

Csize

Ddtype

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'size' directly instead of computing from shape.

Trying to index 'ndim' or 'dtype'.

The product of the values in the shape tuple gives the total number of elements (2 * 3 * 4 = 24).

Practice

1. Which numpy attribute tells you the total number of elements in an array?

easy

A. size

B. shape

C. ndim

D. dtype

Solution

1. Step 1: Understand the meaning of each attribute

   shape shows dimensions, dtype shows data type, ndim shows number of dimensions, and size shows total elements.

2. Step 2: Identify the attribute for total elements

   The attribute size gives the total number of elements in the array.

3. Final Answer:

   size -> Option A

4. Quick Check:

   Total elements = size [OK]

Hint: Total elements? Use size attribute [OK]

Common Mistakes:

• Confusing shape with total elements
• Thinking ndim gives total elements
• Mixing dtype with size

2. Which of the following is the correct way to get the number of dimensions of a numpy array arr?

easy

A. arr.size()

B. arr.ndim

C. arr.shape()

D. arr.dtype

Solution

1. Step 1: Recall attribute vs method syntax in numpy

   Attributes like ndim and dtype are accessed without parentheses, methods like size() do not exist.

2. Step 2: Identify correct attribute for number of dimensions

   arr.ndim gives the number of dimensions directly.

3. Final Answer:

   arr.ndim -> Option B

4. Quick Check:

   Number of dimensions = arr.ndim [OK]

Hint: Use attribute without () for ndim, size, dtype [OK]

Common Mistakes:

• Using parentheses with attributes
• Confusing shape with ndim
• Trying to call size() as method

3. Given the code:

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr.shape, arr.dtype, arr.ndim, arr.size)

What is the output?

medium

A. (2, 3) float64 2 6

B. (3, 2) int64 2 6

C. (2, 3) int64 2 6

D. (2, 3) int32 2 6

Solution

1. Step 1: Analyze the array shape and data type

   The array has 2 rows and 3 columns, so shape is (2, 3). The default integer type on many systems is int64.

2. Step 2: Check number of dimensions and total size

   It is a 2D array, so ndim = 2. Total elements = 2*3 = 6.

3. Final Answer:

   (2, 3) int64 2 6 -> Option C

4. Quick Check:

   shape=(2,3), dtype=int64, ndim=2, size=6 [OK]

Hint: Shape = rows x columns, size = product of shape [OK]

Common Mistakes:

• Mixing rows and columns in shape
• Assuming dtype is int32 by default
• Confusing ndim with size

4. What is wrong with this code snippet?

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

medium

A. print cannot display tuples

B. arr is not defined

C. shape returns a number, not a tuple

D. shape is an attribute, not a method; remove parentheses

Solution

1. Step 1: Identify usage of shape

   shape is an attribute, so it should be accessed without parentheses.

2. Step 2: Correct the code

   Change arr.shape() to arr.shape to fix the error.

3. Final Answer:

   shape is an attribute, not a method; remove parentheses -> Option D

4. Quick Check:

   Attributes have no () [OK]

Hint: Attributes like shape have no () [OK]

Common Mistakes:

• Using parentheses with attributes
• Thinking shape returns a single number
• Assuming print can't show tuples

5. You have a numpy array arr with shape (4, 5, 6). Which attribute would you use to find the total number of elements, and what is that number?

hard

A. arr.size, 120

B. arr.ndim, 3

C. arr.shape, (4, 5, 6)

D. arr.dtype, depends on data

Solution

1. Step 1: Understand the attributes

   size gives total elements, ndim gives number of dimensions, shape gives dimensions, dtype gives data type.

2. Step 2: Calculate total elements from shape

   Total elements = 4 * 5 * 6 = 120, so arr.size = 120.

3. Final Answer:

   arr.size, 120 -> Option A

4. Quick Check:

   Total elements = product of shape = 120 [OK]

Hint: Multiply shape dimensions or use size [OK]

Common Mistakes:

• Confusing ndim with total elements
• Using shape instead of size
• Ignoring that dtype is unrelated to size