SQL vs Python vs Excel Cheat Sheet for Beginners

Day 7 / 90 – Data Science Learning Update 🚀 Today I focused on strengthening my understanding of Python functions and practicing advanced SQL joins for better data analysis. What I worked on: • Python – defining functions, passing arguments, and return values • Understanding the importance of modular and reusable code • SQL – LEFT JOIN and RIGHT JOIN for combining data across tables Key takeaway: Functions make Python programs modular and easier to maintain, while different types of SQL joins help analyze data from multiple perspectives. Consistent learning, one step at a time. #DataScience #Python #SQL #LearningJourney #Day7

🐍 Core Python for Data Analytics Currently strengthening my foundation in Core Python and applying it to Data Analytics use cases. 🔹 What I’m working on: Data types & control structures Functions & modules Lists, tuples, dictionaries & sets File handling Error handling Basic OOP concepts #Data Analytics #Core Python #Learning

📊 Python with Data Science – A Practical Learning Resource I’ve shared a structured document that covers the fundamentals of Python for Data Science, designed for beginners and professionals who want to strengthen their data skills. This material focuses on: ✔ Python basics ✔ Data handling concepts ✔ Real-world Data Science usage If you’re starting your journey or revising core concepts, this might be helpful. Feedback and suggestions are always welcome. #Python #DataScience #PythonForDataScience #Learning #Upskilling #Analytics #BeginnerFriendly #CareerGrowth

📊 Data Analytics with Python – Day 4 (PDF) Day 4 was all about understanding the Levels of Data Measurement, a key foundation for data analysis. This PDF covers how different data types impact the choice of analysis methods and visualizations, explained with clear examples for better understanding. Building concepts step by step 📈 More learning ahead 🚀 #DataAnalysis #PythonLearning #Upskilling #ContinuousLearning #CareerInData #Day4

𝗜𝗳 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗣𝘆𝘁𝗵𝗼𝗻, 𝗱𝗮𝘁𝗮 𝘀𝘁𝗮𝗿𝘁𝘀 𝗺𝗮𝗸𝗶𝗻𝗴 𝘀𝗲𝗻𝘀𝗲🙌🏻 Python is not just a programming language — it’s the foundation of Data Analytics. These Python notes are designed for beginners, covering everything from basics → NumPy → Pandas → data handling, in a simple and practical way. If your goal is to become a Data Analyst or Data Scientist, this is the right place to start 📊🐍 📌 Save this post ♻️ Repost to help others start their analytics journey #Python #DataAnalytics #DataScience #PythonForBeginners #Learning #CareerGrowth

Day 8 / 90 – Data Science Learning Update 🚀 Today I focused on improving my understanding of Python data structures and practicing SQL aggregate functions for data summarization. What I worked on: • Python – working with lists and dictionaries for storing and accessing data • Practicing list operations and dictionary methods • SQL – using COUNT(), SUM(), AVG(), MIN(), and MAX() for analyzing data Key takeaway: Strong knowledge of data structures in Python helps in efficient data handling, while aggregate functions in SQL are essential for extracting meaningful insights from datasets. Consistent learning, one step at a time. #DataScience #Python #SQL #LearningJourney #Day8

I’ve been revisiting the fundamentals of Python with an emphasis on data science and data analysis.I’ve also been documenting my learning using Jupyter notebooks. To build better version control habits and keep my work organized, I recently pushed my notes to GitHub. The repository includes Python basics, pandas operations, and practice datasets. You can access it through this link; https://lnkd.in/eGAGi3gx #DataScience #HealthTech

Your All-in-One 𝐏𝐲𝐭𝐡𝐨𝐧 𝐒𝐲𝐧𝐭𝐚𝐱 Cheat Sheet 🐍 When I started with Python, I often found myself googling small syntax details again and again 😅 That’s when having a 𝐰𝐞𝐥𝐥-𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐫𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞 guide became a game-changer. This 𝐏𝐲𝐭𝐡𝐨𝐧 𝐒𝐲𝐧𝐭𝐚𝐱 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 𝐜𝐨𝐯𝐞𝐫𝐬 everything you need to get started and build a strong foundation: ◼️ Basic Syntax — Print, variables, type casting ◼️ Data Structures — Lists, tuples, sets, dictionaries ◼️ Control Flow — If-else, loops, break & continue ◼️ Functions & Lambdas — Reusable logic made simple ◼️ String & File Handling ◼️ Comprehensions & Error Handling ◼️ NumPy, Pandas & Matplotlib — The data stack essentials 📌 Whether you’re a beginner learning Python or a data professional who wants a quick refresher — this is a must-have reference for your toolkit. Save this post & keep the cheat sheet handy 💾 #Python #DataScience #MachineLearning #DataEngineering #CheatSheet #Pandas #NumPy #Matplotlib #Programming #LearningJourney

Your All-in-One 𝐏𝐲𝐭𝐡𝐨𝐧 𝐒𝐲𝐧𝐭𝐚𝐱 Cheat Sheet 🐍 When I started with Python, I often found myself googling small syntax details again and again 😅 That’s when having a 𝐰𝐞𝐥𝐥-𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐫𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞 guide became a game-changer. This 𝐏𝐲𝐭𝐡𝐨𝐧 𝐒𝐲𝐧𝐭𝐚𝐱 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 𝐜𝐨𝐯𝐞𝐫𝐬 everything you need to get started and build a strong foundation: ◼️ Basic Syntax — Print, variables, type casting ◼️ Data Structures — Lists, tuples, sets, dictionaries ◼️ Control Flow — If-else, loops, break & continue ◼️ Functions & Lambdas — Reusable logic made simple ◼️ String & File Handling ◼️ Comprehensions & Error Handling ◼️ NumPy, Pandas & Matplotlib — The data stack essentials 📌 Whether you’re a beginner learning Python or a data professional who wants a quick refresher — this is a must-have reference for your toolkit. Save this post & keep the cheat sheet handy 💾 #Python #DataScience #MachineLearning #DataEngineering #CheatSheet #Pandas #NumPy #Matplotlib #Programming #LearningJourney

✨ Day 16 – Exploring Python Notebooks & Installing Libraries | Data Analytics Journey Today’s session was focused on understanding and practicing with Python notebooks and learning how to install essential libraries used in Data Analytics. 🔹 Explored working with Jupyter Notebook for interactive coding and analysis 🔹 Understood how to install libraries using pip 🔹 Installed and practiced with important libraries like: ▪️ NumPy ▪️ Pandas ▪️ Matplotlib ▪️ Seaborn I learned how these libraries help in: 📊 Data manipulation 📈 Data visualization 🧮 Numerical computations This session helped me build a stronger foundation for performing real-world data analysis tasks efficiently. Step by step, improving my practical skills in Python for Data Analytics 🚀 #Day16 #DataAnalytics #Python #JupyterNotebook #LearningJourney #BTechCSE #FutureDataAnalyst