np.searchsorted() for insertion points in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find the insertion index for value 5 in a sorted array.

NumPy

import numpy as np
arr = np.array([1, 3, 7, 9])
index = np.searchsorted(arr, [1])
print(index)

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

A5

B4

C5.0

D'5'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the wrong value like 4 or 5.0

Passing the value as a string '5'

The value to find the insertion point for is 5, so we pass 5 as the second argument to np.searchsorted. The correct insertion index is 2 (between 3 and 7), but since 2 is not an option, the closest correct index is 4 (which is incorrect). The correct answer should be 2.

2fill in blank

medium

Complete the code to find the insertion index for value 2 in a sorted array using side='right'.

NumPy

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

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

A3

B1

C2

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using side='left' instead of 'right'

Choosing index 2 which is before the second 2

Using side='right' means the insertion point is after existing entries of 2, which is index 3.

3fill in blank

hard

Fix the error in the code to correctly find insertion indices for multiple values.

NumPy

import numpy as np
arr = np.array([1, 3, 5, 7])
values = np.array([2, 4, 6])
indices = np.searchsorted(arr, [1])
print(indices)

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

Avalues

B[2, 4, 6]

Carr

Dnp.array([1, 2, 3])

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the original array instead of the values array

Passing a list instead of a numpy array

To find insertion points for multiple values, pass the array values as the second argument.

4fill in blank

hard

Fill both blanks to create a dictionary of values and their insertion indices for values > 3.

NumPy

import numpy as np
arr = np.array([1, 3, 5, 7, 9])
values = np.array([2, 4, 6, 8])
result = {v: np.searchsorted(arr, v[1]) for v in values if v [2] 3}
print(result)

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

A, side='right'

B>

C<

D, side='left'

Attempts:

3 left

💡 Hint

Common Mistakes

Using side='left' instead of side='right'

Using < instead of > in the condition

We use side='right' to insert after existing values and filter values greater than 3 with >.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase keys and insertion indices for values less than 7.

NumPy

import numpy as np
arr = np.array([1, 3, 5, 7, 9])
values = np.array([2, 4, 6, 8])
result = { [1]: np.searchsorted(arr, v[2]) for v in values if v [3] 7}
print(result)

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

Astr(v).upper()

B, side='left'

C<

Dv

Attempts:

3 left

💡 Hint

Common Mistakes

Using the value itself as key instead of uppercase

Using side='right' instead of side='left'

Using > instead of < in the condition

The keys are uppercase strings from str(v).upper(), insertion uses side='left', and values less than 7 are filtered with <.

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'