Record arrays in NumPy - Mini Project: Build & Apply

Working with Record Arrays in NumPy

📖 Scenario: Imagine you work in a small library. You want to keep track of books with their title, author, and year published. You will use a special kind of array called a record array to store this information neatly.

🎯 Goal: Create a NumPy record array to store book information, then select and display books published after a certain year.

📋 What You'll Learn

Create a NumPy record array with fields: 'title' (string), 'author' (string), and 'year' (integer).

Create a variable to hold the year threshold for filtering books.

Use a condition to select books published after the threshold year.

Print the filtered record array showing only those books.

💡 Why This Matters

🌍 Real World

Record arrays help store mixed data types in one array, useful for datasets like books, employees, or products.

💼 Career

Understanding record arrays is important for data scientists and analysts who work with structured data in NumPy.

1

Create a NumPy record array with book data

Create a NumPy record array called books with these exact entries: ('The Hobbit', 'J.R.R. Tolkien', 1937), ('1984', 'George Orwell', 1949), and ('To Kill a Mockingbird', 'Harper Lee', 1960). Use the data types 'U20' for title and author, and int for year.

NumPy

import numpy as np
# Create the record array 'books' with the given data and data types
# Your code here

Need a hint?

Use np.array with a list of tuples and specify the dtype as a list of tuples for field names and types.

2

Set a year threshold for filtering books

Create a variable called year_threshold and set it to 1940.

NumPy

import numpy as np
books = np.array([
    ('The Hobbit', 'J.R.R. Tolkien', 1937),
    ('1984', 'George Orwell', 1949),
    ('To Kill a Mockingbird', 'Harper Lee', 1960)
], dtype=[('title', 'U20'), ('author', 'U20'), ('year', int)])

# Create the variable 'year_threshold' and set it to 1940
# Your code here

Need a hint?

Just create a variable named year_threshold and assign the number 1940 to it.

3

Select books published after the threshold year

Create a variable called recent_books that selects from books only those entries where the year is greater than year_threshold.

NumPy

import numpy as np
books = np.array([
    ('The Hobbit', 'J.R.R. Tolkien', 1937),
    ('1984', 'George Orwell', 1949),
    ('To Kill a Mockingbird', 'Harper Lee', 1960)
], dtype=[('title', 'U20'), ('author', 'U20'), ('year', int)])
year_threshold = 1940

# Select books with year greater than year_threshold into 'recent_books'
# Your code here

Need a hint?

Use boolean indexing with books['year'] > year_threshold to filter the record array.

4

Print the filtered record array

Write a print statement to display the recent_books record array.

NumPy

import numpy as np
books = np.array([
    ('The Hobbit', 'J.R.R. Tolkien', 1937),
    ('1984', 'George Orwell', 1949),
    ('To Kill a Mockingbird', 'Harper Lee', 1960)
], dtype=[('title', 'U20'), ('author', 'U20'), ('year', int)])
year_threshold = 1940
recent_books = books[books['year'] > year_threshold]

# Print the 'recent_books' record array
# Your code here

Need a hint?

Use print(recent_books) to show the filtered books.