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.

Practice

1. What does the np.searchsorted() function do in NumPy?

easy

A. Returns the maximum value in the array

B. Sorts the array in ascending order

C. Removes duplicate values from the array

D. Finds the index where a value should be inserted to keep the array sorted

Solution

1. Step 1: Understand the purpose of np.searchsorted()

   This function finds the position where a new element can be inserted in a sorted array without breaking the order.

2. Step 2: Compare with other options

   Options B, C, and D describe different functions: sorting, removing duplicates, and finding max, which are not what searchsorted does.

3. Final Answer:

   Finds the index where a value should be inserted to keep the array sorted -> Option D

4. Quick Check:

   Insertion index finder = A [OK]

Hint: Remember: searchsorted finds insert position, not sorting [OK]

Common Mistakes:

• Confusing searchsorted with sorting functions
• Thinking it removes duplicates
• Assuming it returns values instead of indices

2. Which of the following is the correct syntax to find the insertion index of value 5 in a sorted array arr using np.searchsorted()?

easy

A. np.searchsorted(arr, value=5)

B. np.searchsorted(arr, 5)

C. arr.searchsorted(5)

D. np.searchsorted(5, arr)

Solution

1. Step 1: Recall the function signature

   The correct syntax is np.searchsorted(array, value), so the array comes first, then the value.

2. Step 2: Check each option

   np.searchsorted(arr, 5) matches the correct order. np.searchsorted(5, arr) reverses arguments. arr.searchsorted(5) is invalid because searchsorted is not a method of ndarray. np.searchsorted(arr, value=5) uses a wrong keyword argument.

3. Final Answer:

   np.searchsorted(arr, 5) -> Option B

4. Quick Check:

   Array first, value second = D [OK]

Hint: Remember: np.searchsorted(array, value) order [OK]

Common Mistakes:

• Swapping the order of arguments
• Using searchsorted as a method of array
• Using incorrect keyword arguments

3. What is the output of the following code?

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

medium

A. 2

B. 1

C. 3

D. 4

Solution

1. Step 1: Understand the array and value

   The array is [1, 3, 5, 7], and we want to insert 4 while keeping it sorted.

2. Step 2: Find the insertion index

   4 fits between 3 (index 1) and 5 (index 2), so the insertion index is 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Insert 4 between 3 and 5 = 2 [OK]

Hint: Find where value fits between sorted elements [OK]

Common Mistakes:

• Choosing index of smaller element
• Choosing index of larger element
• Confusing zero-based indexing

4. The code below throws an error. What is the mistake?

import numpy as np
arr = np.array([2, 4, 6, 8])
index = np.searchsorted(arr, side='left', 5)
print(index)

medium

A. The 'side' argument should come after the value argument

B. The array must be sorted in descending order

C. The function does not accept keyword arguments

D. The value to insert must be an array, not a scalar

Solution

1. Step 1: Check function argument order

   np.searchsorted expects the array first, then the value, then optional keywords like side.

2. Step 2: Identify the error in argument placement

   The code passes side='left' before the value 5, which is incorrect syntax.

3. Final Answer:

   The 'side' argument should come after the value argument -> Option A

4. Quick Check:

   Keyword args after positional args = A [OK]

Hint: Put keyword arguments after positional ones [OK]

Common Mistakes:

• Placing keyword arguments before positional arguments
• Assuming array must be descending
• Thinking scalar values are invalid

5. Given a sorted array arr = np.array([1, 2, 2, 3, 4]), which code snippet will insert the value 2 after all existing 2s using np.searchsorted()?

hard

A. index = np.searchsorted(arr, 2)

B. index = np.searchsorted(arr, 2, side='left')

C. index = np.searchsorted(arr, 2, side='right')

D. index = np.searchsorted(arr, 2, side='both')

Solution

1. Step 1: Understand the side parameter

   side='right' returns the insertion index after existing equal values; side='left' inserts before.

2. Step 2: Apply to the array

   For value 2 in [1, 2, 2, 3, 4], side='right' gives index 3, after the two 2s.

3. Final Answer:

   index = np.searchsorted(arr, 2, side='right') -> Option C

4. Quick Check:

   Insert after equals = side='right' = C [OK]

Hint: Use side='right' to insert after equal values [OK]

Common Mistakes:

• Using side='left' inserts before equal values
• Assuming default side inserts after equals
• Using invalid side='both'