Data Analytics
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Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.

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πŸ“Œ How to Build a Rate Limiter with Redis and Python to Scale Your Apps

✍️ Sravan Karuturi
🏷️ #Python
πŸ“Œ How to Work with Environment Variables in Python

✍️ Bala Priya C
🏷️ #Python
πŸ“Œ How to Parse INI Config Files in Python with Configparser

✍️ Bala Priya C
🏷️ #Python
πŸ“Œ How to Turn Websites into LLM-Ready Data Using Firecrawl

✍️ Manish Shivanandhan
🏷️ #Python
πŸ“Œ How to Work with TOML Files in Python

✍️ Bala Priya C
🏷️ #Python
πŸ“Œ Build a Website Screenshot Generator with Python and Flask

✍️ Ashutosh Krishna
🏷️ #Python
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πŸ“Œ How to Parse JSON in Python – A Complete Guide With Examples

✍️ Bala Priya C
🏷️ #Python
πŸ“Œ How to Build Your Own MCP Server with Python

✍️ Manish Shivanandhan
🏷️ #Python
πŸ“Œ How to Manage Python Packages with uv

✍️ Hew Hahn
🏷️ #Python
πŸ“Œ How to Parse XML in Python Without Using External Libraries

✍️ Bala Priya C
🏷️ #Python
πŸ“Œ How to Manage Your Python Projects with Poetry

✍️ Manish Shivanandhan
🏷️ #Python
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All Cheat Sheets Collection (3).pdf
2.7 MB
Python For Data Science Cheat Sheet

#python #datascience #DataAnalysis

https://t.me/CodeProgrammer

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Numpy @CodeProgrammer.pdf
2.4 MB
🏷 Sections of the «NumPy» library
⬅️ From introductory to advanced


πŸ‘¨πŸ»β€πŸ’» This is a long-term project to learn Python and NumPy from scratch. The main task is to handle numerical #data and #arrays in #Python using NumPy, and many other libraries are also used.


✏️ This section shows a structured and complete path for learning #NumPy; but the code examples and exercises help to practically memorize the concepts.


⭕️ Introduction to NumPy
🟠 NumPy arrays
⭕️ Introduction to array features
🟠 Basic operations on arrays
⭕️ Functions for statistical and aggregative purposes
🟠 And...

https://t.me/CodeProgrammer β›ˆβš‘οΈ
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Mastering pandas%22.pdf
1.6 MB
🌟 A new and comprehensive book "Mastering pandas"

πŸ‘¨πŸ»β€πŸ’» If I've worked with messy and error-prone data this time, I don't know how much time and energy I've wasted. Incomplete tables, repetitive records, and unorganized data. Exactly the kind of things that make analysis difficult and frustrate you.

⬅️ And the only way to save yourself is to use pandas! A tool that makes processes 10 times faster.

🏷 This book is a comprehensive and organized guide to pandas, so you can start from scratch and gradually master this library and gain the ability to implement real projects. In this file, you'll learn:

πŸ”Ή How to clean and prepare large amounts of data for analysis,

πŸ”Ή How to analyze real business data and draw conclusions,

πŸ”Ή How to automate repetitive tasks with a few lines of code,

πŸ”Ή And improve the speed and accuracy of your analyses significantly.

🌐 #DataScience #DataScience #Pandas #Python

https://t.me/CodeProgrammer ⚑️
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