Variables, Data Types, and Input Handling

# CHAPTER 6

Variables, Data Types, and Input Handling #

1. Chapter Introduction #

2. Variables in Python #

A variable is like a labeled box where you store data. In Python, you don't need to declare the type of data beforehand (unlike Java or C++). You just assign a value using the equals sign =.

Cell 1:

# Creating variables
customer_name = "Alice"
age = 28
is_premium_member = True

# Displaying variables
print(customer_name)

*Output: Alice*

Naming Rules:

• Must start with a letter or underscore ().

• Can only contain alphanumeric characters and underscores (A-z, 0-9, and ).

• Case-sensitive (age, Age, and AGE are three different variables).

• *Best Practice:* Use snake_case (all lowercase, separated by underscores) for Python variables.

3. Core Data Types #

Python has four primary primitive data types. You can always check a variable's type using the built-in type() function.

Cell 2:

# 1. Integer (Whole numbers)
quantity = 50
print(type(quantity))

# 2. Float (Decimals)
price = 19.99
print(type(price))

# 3. String (Text, wrapped in single or double quotes)
product_id = "ITEM-4421"
print(type(product_id))

# 4. Boolean (True or False)
in_stock = False
print(type(in_stock))

4. Type Conversion (Casting) #

Often, data comes in the wrong format (e.g., a number is stored as text). You must convert it before doing math.

Cell 3:

# A number stored as a string
string_num = "100"

# This will cause an error: string_num + 50 (Cannot add text and numbers)

# Convert string to integer
real_num = int(string_num)
print(real_num + 50)  # Output: 150

# Convert integer to string
new_string = str(real_num) + " dollars"
print(new_string)     # Output: 100 dollars

# Convert integer to float
decimal_num = float(real_num)
print(decimal_num)    # Output: 100.0

5. String Formatting (f-strings) #

When building reports in Jupyter, you frequently need to combine variables with text. The modern and most readable way to do this in Python is using f-strings (formatted string literals). Place an f before the quotes and use curly braces {} for variables.

Cell 4:

user = "David"
logins = 12

# Using an f-string
message = f"User {user} has logged in {logins} times this month."
message

*Output: 'User David has logged in 12 times this month.'*

6. Interactive Input Handling #

Because Jupyter is interactive, you can actually pause the Kernel and ask the user to type something into a text box right inside the notebook!

Cell 5:

# The input() function pauses execution and waits for the user
user_age = input("Please enter your age: ")

print(f"You entered: {user_age}")
print(type(user_age)) 

*Note: The input() function ALWAYS returns a String, even if the user types a number. You must cast it to an int if you want to do math.*

Cell 6:

# Proper way to handle numeric input
birth_year = input("Enter your birth year: ")
age_in_2030 = 2030 - int(birth_year)
print(f"In 2030, you will be {age_in_2030} years old.")

7. Common Mistakes #

• The Kernel Hangs on Input: If you run an input() cell, Jupyter stops and waits. If you don't realize this and try to run the next cell, it will just queue up (showing In [*]). If your notebook is stuck, check if it is waiting for an input box to be filled!

• Using reserved keywords: Don't name your variables print, list, str, or int. This overwrites the built-in Python functions for that specific Kernel session.

8. MCQs #

• Q: A user enters "10" into an input() prompt. You try to run result = userinput * 2 and the output is "1010". What happened and how do you fix it?

10. Summary #

11. Next Chapter Recommendation #