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This repo showcases my learning compilation with IBM's Python for Data Science course! 🚀 Over 500 lines of code here, mixed with my own spices—think hip-hop culture and cellular biology references. Heads up, some code involves my own docs, so you'll want to tweak those parts. Got questions or wanna geek out over Python for Data Science? Hit me up!

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Python-For-Data-Science-by-IBM

TL;DR

This repo showcases my learning compilation with IBM's Python for Data Science course! 🚀 Over 500 lines of code here, mixed with my own spices—think hip-hop culture and cellular biology references. Heads up, some code involves my own docs, so you'll want to tweak those parts. Got questions or wanna geek out over Python for Data Science? Hit me up!

The complete picture:

This repository is a compilation of my learnings from taking the "Python for Data Science" course offered by IBM, an 18-hour-long course available on Cognitive Class at the following link: https://cognitiveclass.ai/courses/python-for-data-science.

The course is structured into five distinct modules:

  1. Python Basics
  2. Python Data Structures
  3. Python Programming Fundamentals
  4. Working with Data in Python
  5. Working with NumPy Arrays and Simple APIs

The code in this repository is inspired by the classes, but I have modified most of it, infusing a lot of creativity, including references to hip-hop and cellular biology; these are subjects that represent my personal interests.

Having been exposed to Python previously, I focused on documenting concepts and techniques that were either new to me or that deepened my existing understanding, such as the use of custom functions, certain control flows, and the creation of new classes.

In this repository, which contains over 500 lines of code, you'll find sections on:

1. String Operations 2. Regular Expressions (RegEx) and Special Expressions 3. Tuples and Lists 4. Sets 5. Dictionaries 6. Branching 7. For & While Loops 8. Custom Functions 9. Classes 10. Manipulation of a TXT File 11. Pandas 12. NumPy 13. 2D Arrays (NumPy) 14. APIs

Many of these sections include subsections.Each new section begins with its title in capital letters and is separated by blank lines above and below for easy identification.

Please note, there are lines of code that utilize internal documents from my computer storage, which will not execute on your computer. I recommend editing the code with your own materials. For example, I used simple Google Docs and Sheets documents, which could be an excellent practice for you if you're interested in learning more.

Line 275, under "Manipulating a TXT File," where I used a Google Doc. Line 326, under "Pandas," where I used a simple Google Sheet with two columns: one for the names of selected theories of aging and another for the years they were proposed. Line 352, under "Pandas," where I used a simple Google Sheet with two columns: one for the names of selected companies and another for their years of foundation.

If you have any questions or need further clarification, don't hesitate to reach out. I'll be glad to help!

About

This repo showcases my learning compilation with IBM's Python for Data Science course! 🚀 Over 500 lines of code here, mixed with my own spices—think hip-hop culture and cellular biology references. Heads up, some code involves my own docs, so you'll want to tweak those parts. Got questions or wanna geek out over Python for Data Science? Hit me up!

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