Accessing APIs with Python: Retrieving Data and JSON

DB Administration in SQL through a Python package. Building out one piece of a larger data pipeline—establishing local database connections, creating structured tables, inserting records, and querying live data directly from Python. This is where application logic meets data infrastructure, turning code into systems that store, validate, and move real information. More to come as the system continues to expand. #fscj #aiprogram #python #ai #data

SQL or Python — which one should you learn for data analysis? 🤔 The truth is: you don’t have to choose one over the other. 🔹 SQL helps you extract and manage structured data 🔹 Python helps you analyze, automate, and visualize it Together, they make a powerful combo for any data professional. 💡 Start with SQL for data handling, then level up with Python for deeper insights. #DataAnalytics #SQL #Python #DataScience #LearningJourney

Bridging Python Data Types with Business Needs: How TPMs, Data Engineers, and Analysts Collaborate on the 'Single Source of Truth'

Working on Real World Data Problems Using Pure Python Recently worked on a project focused on handling and analyzing structured data using core Python without relying on libraries like NumPy or Pandas. The goal was to understand the logic from the ground up. Cleaned and structured raw JSON data Built logic for “People You May Know” (mutual connections) Implemented “Pages You Might Like” recommendations Focused on problem-solving using basic data structures This approach helped me strengthen my core data handling and logical thinking, rather than depending on pre-built tools. Late nights after work, but worth it for the growth. #Python #DataProcessing #DataScience #ProblemSolving #CorePython #Algorithms #NumPy #pandas

Most Python classes I've seen in DS projects do too much! They load data, clean it, transform it, run the model, and log results... all in one place. It feels efficient until you need to change one thing and have to re-test everything else. That's the cost of ignoring the Single Responsibility Principle. 🐍 In my latest article, I break down what SRP actually means for Python data pipelines: https://lnkd.in/esKz_ARk This is post 1 of 5 in a series on SOLID principles applied to Data Science code. What's the messiest class you've inherited on a DS project? 👇 #Python #DataScience #SoftwareEngineering #SOLID #DataEngineering

Turn messy data into actionable business insights with Python. Learn how to clean, analyse, visualise and model data using Python in this hands-on course designed for real-world business problems. Ideal for business and data analysts, programmers and executives looking to strengthen their data capabilities. Sign up now to build practical, in-demand Python data skills: https://lnkd.in/e7nFctEZ NUS Computing #LearnPython #PythonTraining #dataanalytics #businessanalytics #machinelearning #datascience

Python Data Types — One Post Cheat Sheet Understanding data types is fundamental to writing efficient Python code. Here’s a quick overview: 🔢Numeric int → 10 float → 10.5 complex → 2+3j 🔤 String (str) Ordered & immutable Example: "Hello Python" 📋 List Ordered, mutable, allows duplicates Example: [10, 20, 30] 📦 Tuple Ordered, immutable Example: (10, 20, 30) 🔁 Set Unordered, no duplicates Example: {10, 20, 30} 📖 Dictionary Key–value pairs, mutable Example: {"name": "Maha", "age": 25} 🧠 Boolean True / False Used in conditions 🔍 Check Type type(variable) Choosing the right data type improves performance, readability, and data handling. #Python #DataTypes #PythonBasics #Programming #LearnPython #Coding #DataAnalytics #PythonForBeginners

Built a Smart Expense Classifier using Python I worked on analyzing financial transaction data and built a model to automatically categorize expenses. Key learnings: – Data cleaning is crucial – Model accuracy depends heavily on preprocessing – Real-world data is messy but valuable Looking forward to improving this further and building more data-driven solutions. #DataAnalytics #Python #MachineLearning #Projects

Nobody tells Python beginners the truth. Syntax won't get you hired. Pandas will. Loops won't make you an analyst. Cleaning messy data will. The job is nothing like the tutorials. Learn it the way it actually works 👇 🌐 https://lnkd.in/gFJCy7WA Drop a "DATA" in the comments if you want to know where to start. 👇