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https://github.com/tanu-n-prabhu/python

This repository helps you understand python from the scratch.
https://github.com/tanu-n-prabhu/python

data dataanalysis datascraping google-colab google-colab-notebook jupyter-notebook machine-learning numpy numpy-arrays pandas-dataframe prediction python python-3 python3

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This repository helps you understand python from the scratch.

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README 

        


 🐍📊 Welcome to the Python Programming Hub 📊🐍



The Best place to learn Python and Data Science



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| ![space-1.jpg](https://github.com/Tanu-N-Prabhu/Python/blob/master/Img/logo.jpg) | 

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| Image Credits [Wallpaper Flare](https://www.wallpaperflare.com/programming-is-an-art-text-code-python-computer-python-programming-wallpaper-srfia) |



[![Hits](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FTanu-N-Prabhu%2FPython&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=hits&edge_flat=false)](https://hits.seeyoufarm.com)



Welcome to a treasure trove of Python programming expertise 🐍, Data Science mastery 📊, and essential survival skills for navigating the dynamic world of programming 💡. Dive into the depths of this repository to unlock the knowledge and tools you need to thrive in your coding journey 🚀.



## About



This repository isn't just a collection of code snippets 💻; it's a comprehensive resource designed to empower learners 📚 and professionals 👩‍💻👨‍💻 alike. You’ll find invaluable insights and guidance for:



* 🐍 Novices: Explore the fundamentals of Python programming.

* 📊 Data Enthusiasts: Delve into the intricacies of data science.

* 🛠️ Seasoned Developers: Hone your craft with advanced techniques and tips.



## What We Offer



* Python Proficiency 🐍: Elevate your Python skills from beginner to advanced levels with our curated tutorials, exercises, and real-world examples.

* Data Science Expertise 📊: Harness the power of data with our in-depth guides, projects, and best practices in data analysis, machine learning, and beyond.

* Survival Toolkit 🛠️: Navigate the complexities of the programming world with confidence, thanks to our tips, tricks, and advice on career development, productivity, and staying ahead of the curve.

  

## Why Choose this Repository



* Comprehensive Learning 📚: Whether you're starting your journey or aiming for mastery, our repository provides the resources you need to succeed.

* Community Support 🤝: Join a vibrant community of learners, mentors, and experts passionate about sharing knowledge and helping each other grow.

* Practical Application 🛠️: From theory to practice, our hands-on approach ensures that you understand concepts and how to apply them effectively in real-world scenarios.



### Get Involved 🚀



Ready to embark on your Python journey? Explore our repository, contribute your expertise, and connect with fellow enthusiasts. Together, we'll sharpen our skills, unravel the mysteries of programming, and unlock new opportunities in the ever-evolving tech landscape.



## Join Us on this Adventure



The Python Mastery Repository 🐍 is more than just a collection of code; it's a gateway to endless possibilities 🌟. Start your exploration today and discover the boundless potential of Python programming 💻, data science 📊, and beyond.



# Installation tools



Below are some tools you can download before getting started with Python. It's all about personal preference, so feel free to choose the ones that work best for you! 🛠️



| Name of the tools | 

| ------------- |

|[Python download](https://www.python.org/downloads/)|

|[Visual Studio Code](https://code.visualstudio.com/download)|

|[Jupyter Notebook](https://jupyter.org/install)|

|[Google Colab](https://colab.research.google.com/notebooks/welcome.ipynb)|



I use Google Colab for Python programming, and it's one of the best interactive tools out there 🌟. I love it because it allows me to add more documentation to my code and create quality tutorials, making it easier to share knowledge and improve learning. 📚💻



# Repository Contents



#### This repository is divided into two parts such as Python Coding and Data Science for Beginners.



## Python Coding



Follow the steps down below to get started coding in Python!!!



 






### Pythonic Materials



  Chapter 1️⃣ ⮕ Basic Concepts



 - [Python Input, Output and Import functions](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_Input%2C_Output_and_Import.ipynb)

 

 - [Python Variables](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_Variables.ipynb)

   * [Python Global, Local and Nonlocal Variables](https://github.com/Tanu-N-Prabhu/Python/blob/master/Global%2C_Local_and_Nonlocal_variables_in_Python.ipynb)

   

 - [Python Strings](https://github.com/Tanu-N-Prabhu/Python/tree/master/Strings)

 

 - [Python Lists](https://github.com/Tanu-N-Prabhu/Python/tree/master/Lists) 

 

 - [Python Tuples](https://github.com/Tanu-N-Prabhu/Python/tree/master/Tuples)

 

 -  [Python Dictionary](https://github.com/Tanu-N-Prabhu/Python/tree/master/Dictionary%20)

 

 - [Python Operators](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_Operators.ipynb)



  Chapter 2️⃣ ⮕ Built-in Functions



 - [Python Input, Output and Import built-in-functions](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_Input%2C_Output_and_Import.ipynb)

 

 - [Eval built-in-function](https://github.com/Tanu-N-Prabhu/Python/blob/master/Eval_built_in_function.ipynb)

   

 - [Range built-in-function](https://github.com/Tanu-N-Prabhu/Python/blob/master/Range_built_in_function.ipynb)

 

 - [Python Lambda Function](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_Lambda_Function.ipynb)

 

 - [Python Enumerate Function](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_enumerate()_built_in_function.ipynb)

 

 - [Python len function](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python_len()_built_in_function.ipynb)  

 



  Chapter 3️⃣ ⮕ Libraries



 - [Numpy library](https://github.com/Tanu-N-Prabhu/Python/tree/master/Numpy)

 

 - [Pandas library](https://github.com/Tanu-N-Prabhu/Python/tree/master/Pandas)

   

 - [Math Module](https://github.com/Tanu-N-Prabhu/Python/blob/master/Learn_the_Python_Math_Module.ipynb)

 

 - [JSON library](https://github.com/Tanu-N-Prabhu/Python/blob/master/How_to_handle_JSON_in_Python%3F.ipynb)



  Chapter 4️⃣ ⮕ API's



 - [Google Translate API for Python](https://github.com/Tanu-N-Prabhu/Python/tree/master/Google%20Translate%20API)

 

 - [Google Trends API for Python](https://github.com/Tanu-N-Prabhu/Python/blob/master/Google_Trends_API.ipynb)

   

 - [Wikipedia API for Python](https://github.com/Tanu-N-Prabhu/Python/blob/master/Wikipedia_API_for_Python.ipynb)

 

 - [Google Search API for Python](https://github.com/Tanu-N-Prabhu/Python/blob/master/The_two_Google_Search_Python_Libraries_you_should_never_miss.ipynb)



 - [General Transit Feed Specification - General Transit Feed Specification (GTFS)](https://github.com/Tanu-N-Prabhu/Python/blob/387a2cdd5bcfc4afbae2319d017a850bdaeb772c/Transit_Data_Calgary_2025.ipynb)



  Chapter 5️⃣ ⮕ Additional Materials



 - [How to get started coding in Python?](https://github.com/Tanu-N-Prabhu/Python/blob/master/How_to_get_started_coding_in_Python%3F.ipynb)

 

 - [Is Python Object Oriented?](https://github.com/Tanu-N-Prabhu/Python/blob/master/Is_Python_object_oriented%3F.ipynb)

 

 - [Speech Recognition using Python](https://github.com/Tanu-N-Prabhu/Python/blob/master/Speech_Recognition_using_Python.ipynb)

 

 - [One-Hot encoding in Python](https://github.com/Tanu-N-Prabhu/Python/blob/master/Learning_One_Hot_Encoding_in_Python_the_Easy_Way.ipynb)

 

 - [Reading An Image In Python (Without Using Special Libraries)](https://github.com/Tanu-N-Prabhu/Python/blob/master/Reading_An_Image_In_Python_(Without_Using_Special_Libraries).ipynb)

 

 - [Rendering Images inside a Pandas DataFrame](https://github.com/Tanu-N-Prabhu/Python/blob/master/Rendering_Images_inside_a_Pandas_DataFrame.ipynb)

 

 - [Using the Pandas Data Frame as a Database](https://github.com/Tanu-N-Prabhu/Python/blob/master/Using_the_Pandas_Data_Frame_as_a_Database_.ipynb)

 

 - [Using the Pandas Data Frame in Day-To-Day Life](https://github.com/Tanu-N-Prabhu/Python/blob/master/Using_the_Pandas_DataFrame_in_Day_To_Day_Life.ipynb)

 

 - [Presenting Python code using RISE](https://github.com/Tanu-N-Prabhu/Python/blob/master/Presenting_Python_code_using_RISE.ipynb)

 

 - [Cheat Sheet for Google Colab](https://github.com/Tanu-N-Prabhu/Python/blob/master/Cheat_sheet_for_Google_Colab.ipynb)



 - [Pick-Up Line Generator using Python Dictionaries](https://github.com/Tanu-N-Prabhu/Python/blob/master/Pick_up_Line_Generator.ipynb)

 



  Chapter 6️⃣ ⮕ Exercises



 - [String Concatenation Questions](https://github.com/Tanu-N-Prabhu/Python/blob/master/String_Concatenation_Exercise_Questions.ipynb)

   * [String Concatenation Answers](https://github.com/Tanu-N-Prabhu/Python/blob/master/String_Concatenation_Exercise_Answers.ipynb)

   

 - [Built-In Functions Exercise Questions](https://github.com/Tanu-N-Prabhu/Python/blob/master/Built_In_Functions_Exercise_Questions.ipynb)

 



  Chapter 7️⃣ ⮕ Quiz



 - [Quiz - 1](https://github.com/Tanu-N-Prabhu/Python/blob/master/Quiz/Python_Quiz_1.ipynb)

   

 - [Quiz - 2](https://github.com/Tanu-N-Prabhu/Python/blob/master/Quiz/Python_Quiz_2.ipynb)

 

 - [Quiz - 3](https://github.com/Tanu-N-Prabhu/Python/blob/master/Quiz/Python_Quiz_3.ipynb)

 



  Chapter 8️⃣ ⮕ Interview Preparation



 - [Python Coding Interview Questions (Beginner to Advanced)](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Python%20Coding%20Interview%20Questions%20(Beginner%20to%20Advanced).md)

 

 - [35 Python interview questions for experienced](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/35%20Python%20interview%20questions%20for%20experienced.md)



-  [Python Interview Questions - Strings](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Python_Interview_Questions_and_Answers_Strings.md)



 -  [Python Theoretical Interview Questions](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Python_Theoritical_Interview_Questions.md)



-  [15 Python Interview Questions and Answers](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Python_Interview_Questions_and_Answers.md) 



- [Assigning Candies to Children Problem with Solution](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Children_with_candy.ipynb)



- [Basic Calculator](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Basic_calculator.ipynb)



-  [Text Justification](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Text_Justification.ipynb)



- [Removing an Element](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Remove_Element.ipynb)



- [Vowel Count in a Sentence](https://github.com/Tanu-N-Prabhu/Python/blob/master/Vowel_Count.ipynb)



- [Pick-Up Line Generator - Based on Sentiments](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/pick_up_line_generator_sentiments.ipynb)



- [Sentimental Analysis](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Sentimental_Analysis.ipynb)



- [Creating a Regular Polygon Visualizer Using Matplotlib in Python](https://github.com/Tanu-N-Prabhu/Python/blob/master/Python%20Coding%20Interview%20Prep/Draw_polygon.ipynb)



   



👉 **Expand** and **Collapse** the above Chapters for more details

  

---



  

## Data Science



Follow the steps below to get started learning Data Science!!!










### Data Science Materials



  Data Exploration



 - [Loading a File using Pandas](https://github.com/Tanu-N-Prabhu/Python/blob/master/data_load.md)

 

 



  Data Scraping from the Web



 - [Scraping Two YouTube Accounts - PewDiePie vs T-Series](https://github.com/Tanu-N-Prabhu/Python/blob/master/Data%20Scraping%20from%20the%20Web/Scraping%20YouTube%20accounts%20with%20python.ipynb)

 

 - [Scraping Rate My Professor Website - My Graduate Professor](https://github.com/Tanu-N-Prabhu/Python/blob/master/Data%20Scraping%20from%20the%20Web/Web_Scraping_Rate_My_Professor_Website.ipynb)



 - [Web Scraping vs API: Which Data Extraction Method is Best for Your Needs?](https://github.com/Tanu-N-Prabhu/Python/blob/master/Data%20Scraping%20from%20the%20Web/Web_Scraping_Vs_API.md)

 




  Cracking Transit Data — Calgary 2025

  

 - [How to Decode and Leverage GTFS for Real-Time Transit Insights](https://github.com/Tanu-N-Prabhu/Python/blob/master/Transit_Data_Calgary_2025.ipynb)

 



---



# Tech is Easy

I Tanu Nanda Prabhu, always like simplifying complex things so that others can understand them more easily and better. Researching is my passion, I go through a ton of videos, articles, and tutorials and conclude starting a repository that purely contains tips and tricks for using Google Sheets. I update this repository every week with tons of information that will make your life simple. I am also seeking help from people who want to contribute to my repository. Feel free to Fork it and add updates, I will consider it.



### [Tech Is Easy](https://github.com/Tanu-N-Prabhu/TechIsEasy)



---



# Nbviewer



If the jupyter notebook doesn't load. Don't worry copy and paste the link to [nbviewer](https://nbviewer.jupyter.org). Because most of my jupyter notebooks are not loading.



---

# Contributors



### Currently there are 10 contributors for this repository. Feel free to contribute!





  




> Want to know, how I did this. Refer here for the [docs](https://github.com/Tanu-N-Prabhu/myWebsite.io/blob/master/Docs/Displaying%20Contributors%20Image%20on%20README%20files%20with%20no%20Pain!.md)



---



# Kaggle Datasets



1) [Kaggle Data Sets](https://www.kaggle.com/tanuprabhu/datasets)



---



# HackerRank Exercises - Solved



1) [HackerRank Exercise Solved](https://github.com/Tanu-N-Prabhu/Python/tree/master/Hacker_Rank_Exercises)



---



# Reddit Communities



1) [Python](https://www.reddit.com/r/Python/)

2) [Learn Python](https://www.reddit.com/r/learnpython/)

3) [Python tips](https://www.reddit.com/r/pythontips/)

4) [Python coding](https://www.reddit.com/r/pythoncoding?utm_medium=android_app&utm_source=share)



---



# Submit your articles here



1) [Data Science from Scratch](https://medium.com/data-science-from-scratch)



---



# GPT Librarian 



If you have access to ChatGPT premium, there is a GPT Librarian with access to all files here [here](https://chat.openai.com/g/g-2HlDYwyrW-python-from-scratch)



---



# Contact for help



| Contact        | Info           | 

| ------------- |:-------------:|

| Gmail      | [email protected]  | 

| Facebook       | Tanu N Prabhu      |    

| Instagram     | tanunprabhu   |

| Linkedin     | [Tanu Nanda Prabhu](https://www.linkedin.com/in/tanu-nanda-prabhu-a15a091b5/) |



---



# Reviews



Below given are some of the reviews about this Python GitHub Repository:

 



> ‪Elin Uppström - Senior Lecturer at Uppsala University, Sweden. 


> I found your excellent exercises at your GitHub wile preparing undergraduate course in data analysis. I want to use it in my course.



> ‪Cole Striler - Data Scientist, Founder of Datafied


> I came across your GitHub and love your Jupyter Notebooks, especially the one on "Predicting PewDiePie's daily subscribers". I think you do a great job at explaining your work which is something others can learn.



> Laurence Watson - Co-Founder & CEO, Treebeard


> You have a lot of great Jupyter notebook content on GitHub.



> Poonam Gupta - Math & AP Computer Science Instructor, Brunswick School 


> Thank you so much for posting such helpful posts on GitHub.Many, many thanks for all you do to spread the knowledge.



**Do you like the Repository, Please drop in your precious reviews by shooting an e-mail**.



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# Feedback



[Any Feedback or Suggestions- Please Click Here](https://form.jotform.com/92847563204259)



---



# Star History



[![Star History Chart](https://api.star-history.com/svg?repos=Tanu-N-Prabhu/Python&type=Date)](https://star-history.com/#Tanu-N-Prabhu/Python&Date)



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