np.where() for conditional selection in NumPy - Mini Project: Build & Apply

Using np.where() for Conditional Selection

📖 Scenario: You work in a store that tracks daily sales numbers. You want to quickly find which days had sales above a certain target.

🎯 Goal: Build a small program that uses np.where() to find the days with sales above a target number.

📋 What You'll Learn

Create a numpy array with exact daily sales numbers

Create a variable for the sales target

Use np.where() to find indices where sales exceed the target

Print the indices of days with sales above the target

💡 Why This Matters

🌍 Real World

Stores and businesses often need to quickly find days or items that meet certain conditions, like sales targets, to make decisions.

💼 Career

Data analysts and scientists use conditional selection with numpy to filter and analyze data efficiently.

1

Create the sales data array

Create a numpy array called sales with these exact values: [150, 200, 90, 300, 250]

NumPy

import numpy as np
# Create the numpy array called sales with values [150, 200, 90, 300, 250]
# Your code here

Need a hint?

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

2

Set the sales target

Create a variable called target and set it to 180

NumPy

import numpy as np
sales = np.array([150, 200, 90, 300, 250])
# Create a variable called target and set it to 180
# Your code here

Need a hint?

Just assign the number 180 to the variable target.

3

Use np.where() to find days exceeding the target

Use np.where() with the condition sales > target and assign the result to a variable called days_above_target

NumPy

import numpy as np
sales = np.array([150, 200, 90, 300, 250])
target = 180
# Use np.where() with condition sales > target and assign to days_above_target
# Your code here

Need a hint?

Use np.where(condition) to get indices where the condition is true.

4

Print the days with sales above the target

Print the variable days_above_target to show the indices of days with sales above the target

NumPy

import numpy as np
sales = np.array([150, 200, 90, 300, 250])
target = 180
days_above_target = np.where(sales > target)
# Print days_above_target
# Your code here

Need a hint?

Use print(days_above_target) to display the result.