np.searchsorted() for insertion points in NumPy - Mini Project: Build & Apply

Find Insertion Points Using np.searchsorted()

📖 Scenario: Imagine you have a sorted list of exam scores. You want to find where new students' scores would fit in this list to keep it sorted.

🎯 Goal: You will learn how to use np.searchsorted() to find the correct positions to insert new scores into a sorted array.

📋 What You'll Learn

Create a sorted numpy array called sorted_scores with exact values

Create a numpy array called new_scores with exact values

Use np.searchsorted() with sorted_scores and new_scores to find insertion points

Print the resulting insertion points array

💡 Why This Matters

🌍 Real World

Finding insertion points is useful in ranking systems, scheduling, or any case where you keep data sorted and want to add new entries correctly.

💼 Career

Data scientists often need to insert new data points into sorted datasets efficiently, and <code>np.searchsorted()</code> helps with this task.

1

Create the sorted scores array

Create a numpy array called sorted_scores with these exact values: [55, 65, 75, 85, 95].

NumPy

import numpy as np
# Create the sorted_scores array with values [55, 65, 75, 85, 95]
# Your code here

Need a hint?

Use np.array() to create the array with the exact values.

2

Create the new scores array

Create a numpy array called new_scores with these exact values: [60, 80, 90].

NumPy

import numpy as np
sorted_scores = np.array([55, 65, 75, 85, 95])
# Create the new_scores array with values [60, 80, 90]
# Your code here

Need a hint?

Use np.array() again to create the new scores array.

3

Find insertion points using np.searchsorted()

Use np.searchsorted() with sorted_scores and new_scores to find the insertion points. Store the result in a variable called insertion_points.

NumPy

import numpy as np
sorted_scores = np.array([55, 65, 75, 85, 95])
new_scores = np.array([60, 80, 90])
# Use np.searchsorted() to find insertion points and store in insertion_points
# Your code here

Need a hint?

Call np.searchsorted() with the sorted array first, then the values to insert.

4

Print the insertion points

Print the variable insertion_points to display the positions where new scores fit in the sorted array.

NumPy

import numpy as np
sorted_scores = np.array([55, 65, 75, 85, 95])
new_scores = np.array([60, 80, 90])
insertion_points = np.searchsorted(sorted_scores, new_scores)
# Print the insertion_points array
# Your code here

Need a hint?

Use print(insertion_points) to show the result.