My Data Science Journey

🚀 Stepping into Python: A Beginner's Guide 🐍

Manav Rastogi's photo
Manav Rastogi
·

3 min read

Hey everyone! 🎉 I’ve taken my first step into the world of Python, and I’m excited to share what I’ve learned so far. Python is known for being simple, powerful, and widely used in various fields like web development, data science, and automation. Let’s dive in! 🚀

🔹 What is Python? 🤔

Python is a beginner-friendly programming language that supports multiple paradigms: ✅ Procedural
✅ Object-Oriented
✅ Functional Programming

It has a huge community, an extensive standard library, and tons of third-party packages.

🔹 Keywords in Python 📌

Keywords are special reserved words that cannot be used as variable or function names. Examples: if, else, for, while, def, class, import, return, True, False, None.

🔹 Mutability & Immutability 🔄

📌 Mutable (Can Change): Lists ([]), Dictionaries ({}), Sets ({})
📌 Immutable (Cannot Change): Tuples (()), Strings (""), Integers, Floats

🔹 Operators in Python ➕➖✖️➗

Operators help us perform calculations and comparisons.

✅ Arithmetic: +, -, *, /, %
✅ Comparison: ==, !=, <, >
✅ Logical: and, or, not
✅ Assignment: =, +=, -=, *=

🔹 Type Casting 🔄

Type casting means converting one data type into another.

Examples:

int("10")   # Converts string to integer
float(5)    # Converts integer to float
str(25)     # Converts integer to string

🔹 Conditionals 🛤️

Conditionals help us make decisions in a program.

age = 18
if age >= 18:
    print("You are an adult")
elif age == 17:
    print("Almost there!")
else:
    print("You are a minor")

🔹 Loops 🔄

Loops repeat a block of code multiple times.

🔹 For Loop (Iterates over a sequence)

for i in range(5):
    print(i)

🔹 While Loop (Runs until a condition is false)

count = 0
while count < 5:
    print(count)
    count += 1

🔹 Functions 🛠️

Functions help organize code into reusable blocks.

def greet(name):
    return f"Hello, {name}!"

print(greet("Alice"))

🔹 Iterators & Generators 🔄⚡

📌 Iterator: Used to iterate over collections like lists.

nums = [1, 2, 3]
iter_nums = iter(nums)
print(next(iter_nums))  # Output: 1

📌 Generator: Uses yield for efficient memory usage.

def my_gen():
    yield 1
    yield 2
    yield 3

for num in my_gen():
    print(num)

🔹 Lambda, Map, Reduce, Filter 🏗️

✅ Lambda (Anonymous Function)

square = lambda x: x * x
print(square(5))  # Output: 25

✅ Map (Applies function to all items in iterable)

nums = [1, 2, 3]
print(list(map(lambda x: x * 2, nums)))  # Output: [2, 4, 6]

✅ Reduce (Reduces iterable to a single value)

from functools import reduce
nums = [1, 2, 3]
sum = reduce(lambda x, y: x + y, nums)
print(sum)  # Output: 6

✅ Filter (Filters elements based on condition)

nums = [1, 2, 3, 4, 5]
even_nums = list(filter(lambda x: x % 2 == 0, nums))
print(even_nums)  # Output: [2, 4]

🔥 Want to Explore More?

I’m documenting my journey on GitHub! Check out my repository: Python Repo 📂

I’ll keep updating my learning. Stay tuned! 🚀 Let’s grow together! 😊

#Python #Learning #Coding #Beginners #DataScience #AI

PythonData ScienceAI