Python Tutorial

Hey everyone,

In this repo, I've put together summaries of some great books that really helped me understand Python on a deeper level. The two books I highly recommend are:

• Data Structures and Algorithms in Python
• Python Crash Course by Eric Matthes

Both of these books gave me a super clear and in-depth understanding of Python, and honestly, I had a lot of fun going through them.

Why did I summarize these books?

One of my favorite ways to study is by explaining things to myself. After every video or book chapter, I like to break things down in my own words—it helps me process the information better. I also enjoy writing down my thoughts, and for that, Jupyter Notebook has been a game-changer. It helped me organize my notes in a clean and structured way, which made me really happy.

I haven’t summarized everything yet—some topics and chapters are still left, but I’ll be adding them soon. I hope you find this repo and these summaries helpful.

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Stay Organized

To keep things simple and easy to follow, I'll organize the files and topics properly so you don't get lost.

1. Data Types

Start with the basics:

• Python_Tutorial_Data_Type(Numbers).ipynb
• Python_Tutorial_Data_Type(String).ipynb

2. Lists

Next, get comfortable with lists:

• List_In_Python1.ipynb
• List_In_Python2.ipynb
• List_in_Python3.ipynb
• List_In_Python4.ipynb
• List_In_Python5(With_Loop).ipynb
• Numerical_Lists_In_Python.ipynb
• Slicing_a_List(Part_1).ipynb
• Slicing_a_List(Part_2).ipynb

3. Tuples

Understand how tuples work:

• Tuple.ipynb

4. Conditional Statements

Finally, learn how to control the flow of your programs:

• Pre_Intro_To_if_Statement.ipynb

Hope this helped, even just a little!

Oh, and before I forget—make sure you actually practice and write the code yourself. That’s the best way to learn!

If you’re looking for good platforms to sharpen your skills, I’d recommend:

• LeetCode – Great for coding challenges.
• StrataScratch – Awesome for SQL and data science problems.
• Codeforces – A bit advanced, but good for competitive programming.
• DataCamp – Interactive learning for data science.
• HackerRank – Good for general coding and problem-solving.

That’s it! Just don’t forget to enjoy the process, make progress, and have fun along the way.