Single element access in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Accessing a single element in a 2D NumPy array

What is the output of the following code?

NumPy

import numpy as np
arr = np.array([[10, 20, 30], [40, 50, 60]])
result = arr[1, 2]
print(result)

A 60

B [60]

C 50

D IndexError

💡 Hint

Remember that indexing starts at 0 and you access elements by row and column.

The element at row 1, column 2 is 60 because indexing starts at 0. So arr[1, 2] accesses the second row and third column.

❓ data_output

intermediate

Extracting a single element from a 3D NumPy array

Given the 3D array below, what is the value of arr[0, 1, 2]?

NumPy

import numpy as np
arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
print(arr[0, 1, 2])

A 9

B 5

C 6

D IndexError

💡 Hint

Think of the array as layers, rows, and columns. The first index selects the layer.

arr[0, 1, 2] selects the first layer (index 0), second row (index 1), and third column (index 2), which is 6.

🔧 Debug

advanced

Identify the error in single element access

What error will the following code raise?

NumPy

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

A IndexError: index 3 is out of bounds for axis 0 with size 3

B TypeError: list indices must be integers or slices

C ValueError: too many indices for array

D No error, output is 3

💡 Hint

Check the size of the array and the index used.

The array has indices 0, 1, 2. Accessing index 3 is out of bounds, so it raises an IndexError.

🚀 Application

advanced

Accessing a single element in a masked NumPy array

Given the masked array below, what is the output of masked_arr[1]?

NumPy

import numpy as np
import numpy.ma as ma
arr = np.array([10, 20, 30])
masked_arr = ma.masked_array(arr, mask=[False, True, False])
print(masked_arr[1])

A ValueError

B 20

C masked

D --

💡 Hint

Masked elements show as '--' when printed.

The element at index 1 is masked, so printing it shows '--' indicating a masked value.

🧠 Conceptual

expert

Understanding single element access with fancy indexing

What is the output of the following code?

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
result = arr[[1]][0]
print(result)

A TypeError

B 20

C IndexError

D [20]

💡 Hint

Remember that arr[[1]] returns a 1-element array, then [0] accesses the first element.

arr[[1]] returns an array with one element [20]. Accessing [0] extracts the scalar 20.