np.searchsorted() for insertion points in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Find insertion index with np.searchsorted()

What is the output of this code snippet using np.searchsorted()?

NumPy

import numpy as np
arr = np.array([1, 3, 5, 7])
index = np.searchsorted(arr, 4)
print(index)

A 0

B 2

C 1

D 3

💡 Hint

Think about where 4 fits in the sorted array [1, 3, 5, 7].

The number 4 should be inserted between 3 and 5, which is at index 2.

❓ data_output

intermediate

Multiple insertion points with side='right'

Given the array and values below, what is the output of np.searchsorted() with side='right'?

NumPy

import numpy as np
arr = np.array([2, 4, 4, 4, 6])
values = np.array([4, 5])
indices = np.searchsorted(arr, values, side='right')
print(indices)

A [4 4]

B [3 4]

C [4 3]

D [3 3]

💡 Hint

With side='right', insertion happens after existing equal values.

For value 4, insertion is after the last 4 at index 3, so index 4. For 5, it fits before 6 at index 4.

🔧 Debug

advanced

Identify the error in np.searchsorted usage

What error does this code raise?

NumPy

import numpy as np
arr = np.array([1, 2, 3])
index = np.searchsorted(arr, [2, 3], side='middle')

A ValueError

B TypeError

C SyntaxError

D No error, returns array

💡 Hint

Check if 'side' parameter accepts 'middle'.

The 'side' parameter only accepts 'left' or 'right'. Using 'middle' raises a ValueError.

🧠 Conceptual

advanced

Effect of sorted vs unsorted input array

What happens if you use np.searchsorted() on an unsorted array?

A It returns the indices of the closest values regardless of order.

B It automatically sorts the array before searching, so results are correct.

C It raises a RuntimeError because the array is not sorted.

D It returns insertion indices assuming the array is sorted, leading to incorrect results.

💡 Hint

Think about the assumption np.searchsorted makes about the input array.

np.searchsorted assumes the input array is sorted. If not, the insertion indices will not be correct.

🚀 Application

expert

Find insertion indices for multiple values in a large array

You have a large sorted array arr and a list of values vals. Which code snippet efficiently finds the insertion indices for all values in vals?

NumPy

import numpy as np
arr = np.arange(0, 1000000, 2)
vals = np.array([3, 500000, 999999])

A indices = [np.searchsorted(arr, v) for v in vals]

B indices = np.array([arr.searchsorted(v) for v in vals])

C indices = np.searchsorted(arr, vals)

D indices = np.searchsorted(vals, arr)

💡 Hint

np.searchsorted can take an array of values to search at once.

Option C uses vectorized np.searchsorted which is efficient. Option C works but is slower due to Python loop. Option C is invalid syntax. Option C reverses arguments.