Python : Basics Concepts in Arithmetic, Data Types, and Conditional Logic

Sajjad Rahman - Nov 6 - - Dev Community

If you're new to Python, understanding basic operations, data types, and conditional logic is essential. Let's recap some fundamental topics. We'll explore each topic with examples.


Chapter 1: Arithmetic Operators

Python provides a variety of operators that make it easy to perform mathematical operations. Here’s a quick rundown of the most common operators:

Syntax Action Example Output
* Multiply 4 * 10 40
+ Addition 7 + 9 16
- Subtract 23 - 4 19
/ Division 27 / 3 9
** Power 3 ** 2 9
% Modulo 7 % 4 3

These operators help you work with numbers in your code. Here are some examples:

# Multiplication
result = 4 * 10
print(result)  # Output: 40

# Addition
total = 7 + 9
print(total)  # Output: 16

# Power
squared = 3 ** 2
print(squared)  # Output: 9
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You can also assign values to variables using these operators:

# Define total spend amount
total_spend = 3150.96
print(total_spend)  # Output: 3150.96
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Chapter 2: Data Types and Collections

In Python, you have various ways to store data, each suited to different types of tasks.

  1. Strings: Used for text. You can define a string using either single or double quotes.

    # Defining a string
    customer_name = 'George Boorman'
    print(customer_name)
    
    # Double quotes also work
    customer_name = "George Boorman"
    
  2. Lists: A list is an ordered collection that can contain multiple values.

    # Creating a list
    prices = [10, 20, 30, 15, 25, 35]
    
    # Accessing the first item
    print(prices[0])  # Output: 10
    
  3. Dictionaries: A dictionary stores key-value pairs, allowing you to look up a value based on a key.

    # Creating a dictionary
    products_dict = {
        "AG32": 10,
        "HT91": 20,
        "PL65": 30,
        "OS31": 15,
        "KB07": 25,
        "TR48": 35
    }
    
    # Accessing a value by key
    print(products_dict["AG32"])  # Output: 10
    
  4. Sets and Tuples:

    • Set: A collection of unique elements.
    • Tuple: An immutable list, meaning it cannot be changed after creation.
    # Creating a set
    prices_set = {10, 20, 30, 15, 25, 35}
    
    # Creating a tuple
    prices_tuple = (10, 20, 30, 15, 25, 35)
    

Chapter 3: Conditional Keywords

Python includes several keywords to evaluate conditions, which are essential for decision-making in your code.

Keyword Function
and Evaluate if multiple conditions are true
or Evaluate if one or more conditions are true
in Check if a value exists in a data structure
not Evaluate if a value is not in a data structure

Let's go over some examples to understand these keywords in action:

  1. Using and:
   age = 25
   income = 50000

   # Check if both conditions are true
   if age > 20 and income > 30000:
       print("Eligible for loan")
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  1. Using or:
   day = "Sunday"
   weather = "sunny"

   # Check if either condition is true
   if day == "Saturday" or weather == "sunny":
       print("Let's go to the park!")
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  1. Using in:
   fruits = ["apple", "banana", "cherry"]

   # Check if a value is in the list
   if "apple" in fruits:
       print("Apple is available.")
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  1. Using not:
   vegetables = ["carrot", "potato", "spinach"]

   # Check if a value is not in the list
   if "broccoli" not in vegetables:
       print("Broccoli is not in the list.")
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SUM UP

This overview covered the basics of arithmetic operations, various data types, and conditional keywords in Python. These are fundamental concepts that will help you build more complex programs.

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