Lesson 6.1: Data Mini-Projects – Introduction

Today’s Goals

• Start working with real-world data using Python
• Learn about data structures for data storage
• Introduce file handling for reading datasets

Warm-Up Question

• What kind of data would be fun to explore? (Sports, movies, etc.)

Understanding Data

• Data can come in many forms: lists, dictionaries, CSV files
• Python's data structures are perfect for storing and manipulating it

Simple Dataset Example

# Sample data: List of students and their scores
students = [
    {'name': 'Alice', 'score': 90},
    {'name': 'Bob', 'score': 80},
    {'name': 'Charlie', 'score': 85}
]

# Finding average score
total_score = sum([student['score'] for student in students])
avg_score = total_score / len(students)
print("Average Score:", avg_score)

Key Concepts for Today

• List of dictionaries is a useful format for structured data
• We'll manipulate this data using loops and conditionals

Class Practice

• How would you find the highest score?
• Write the code for it

Working with CSV Files

import csv

# Open and read CSV file
with open('students.csv', mode='r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row)

Class Activity

• Explore CSV files with your own sample dataset
• Print the data from the file and analyze it

Student Challenge

• Use a real-world dataset (movies, sports scores, etc.)
• Perform basic data analysis (averages, maximums, etc.)

Wrap-Up

• Data exploration with Python is powerful
• Next time: We'll dive into more complex datasets and data manipulation techniques