Negative indexing in NumPy - Mini Project: Build & Apply

Negative Indexing with NumPy Arrays

📖 Scenario: You are working with daily temperature data for a week. You want to access specific days using negative indexing, which counts from the end of the data.

🎯 Goal: Learn how to use negative indexing on a NumPy array to access elements from the end.

📋 What You'll Learn

Create a NumPy array with exact temperature values

Create a variable to hold the negative index

Use negative indexing to get the temperature for that day

Print the temperature value

💡 Why This Matters

🌍 Real World

Negative indexing helps quickly access recent data points, like the last few days of temperature, sales, or stock prices, without counting the total length.

💼 Career

Data scientists often use negative indexing to efficiently retrieve recent records from datasets, making data analysis faster and code cleaner.

1

Create a NumPy array with temperatures

Import NumPy as np and create a NumPy array called temps with these exact values: 23, 25, 22, 20, 19, 21, 24.

NumPy

# Import numpy as np and create the array temps
# Your code here

Need a hint?

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

2

Create a variable for negative index

Create a variable called neg_index and set it to -2 to represent the second last day.

NumPy

import numpy as np

temps = np.array([23, 25, 22, 20, 19, 21, 24])

# Create neg_index variable and set it to -2
# Your code here

Need a hint?

Just assign -2 to the variable neg_index.

3

Use negative indexing to get temperature

Create a variable called temp_neg and assign it the value from temps at the negative index neg_index.

NumPy

import numpy as np

temps = np.array([23, 25, 22, 20, 19, 21, 24])

neg_index = -2

# Use negative indexing to get the temperature
# Your code here

Need a hint?

Use temps[neg_index] to get the value at the negative index.

4

Print the temperature from negative index

Print the value of temp_neg to display the temperature for the second last day.

NumPy

import numpy as np

temps = np.array([23, 25, 22, 20, 19, 21, 24])

neg_index = -2

temp_neg = temps[neg_index]

# Print the temperature value
# Your code here

Need a hint?

Use print(temp_neg) to show the temperature.