np.argsort() for sort indices in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.argsort() on a 1D array

What is the output of the following code?

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

NumPy

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

A [0 1 2 3]

B [3 2 1 0]

C [1 3 2 0]

D [1 2 3 0]

💡 Hint

np.argsort() returns the indices that would sort the array in ascending order.

The smallest element is 10 at index 1, then 20 at index 3, then 30 at index 2, and finally 40 at index 0. So the sorted indices are [1, 3, 2, 0].

❓ data_output

intermediate

Number of items in argsort result for 2D array

Given this 2D array, how many elements does np.argsort(arr, axis=1) return?

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

NumPy

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

A (2, 3)

B (3, 2)

C (6,)

D (2,)

💡 Hint

np.argsort with axis=1 sorts each row and returns indices with the same shape as input.

The input array has shape (2, 3). Sorting along axis=1 returns indices for each row, so the output shape is also (2, 3).

🔧 Debug

advanced

Identify the error in argsort usage

What error does this code raise?

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

NumPy

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

A ValueError: operands could not be broadcast together

B TypeError: argsort() got an unexpected keyword argument 'axis'

C No error, prints [0 1 2]

D AxisError: axis 1 is out of bounds for array of dimension 1

💡 Hint

Check the dimension of the array and the axis parameter.

The array is 1D, so axis=1 is invalid. This causes an AxisError.

🚀 Application

advanced

Using np.argsort() to sort one array by another

You have two arrays:

import numpy as np
names = np.array(['Bob', 'Alice', 'Eve'])
scores = np.array([85, 95, 90])

How do you get the names sorted by their scores in ascending order?

NumPy

import numpy as np
names = np.array(['Bob', 'Alice', 'Eve'])
scores = np.array([85, 95, 90])
sorted_names = names[np.argsort(scores)]
print(sorted_names)

A ['Bob' 'Eve' 'Alice']

B ['Bob' 'Alice' 'Eve']

C ['Eve' 'Bob' 'Alice']

D ['Alice' 'Eve' 'Bob']

💡 Hint

Use np.argsort on scores to get indices that sort scores, then index names with those indices.

np.argsort(scores) returns indices [0, 2, 1] which sorts scores ascending. Indexing names with this gives ['Bob', 'Eve', 'Alice'].

🧠 Conceptual

expert

Understanding np.argsort() with kind parameter

Which statement about the 'kind' parameter in np.argsort() is correct?

A 'kind' is used to specify the data type of the output indices.

B 'kind' specifies the sorting algorithm and can affect stability of the sort.

C 'kind' controls the axis along which sorting is performed.

D 'kind' determines whether the output is sorted ascending or descending.

💡 Hint

Think about sorting algorithms and their properties.

The 'kind' parameter lets you choose the sorting algorithm (e.g., 'quicksort', 'mergesort'). Some algorithms are stable, others are not.