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

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.

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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

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)
   

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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")

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!")

1. Using in:

   fruits = ["apple", "banana", "cherry"]

   # Check if a value is in the list
   if "apple" in fruits:
       print("Apple is available.")

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.