Pandas loc vs iloc: Know the Difference

A quick #geopandas cheat sheet on - and if you want to learn all of these (and a lot) more in Python, then: 𝐆𝐞𝐨𝐬𝐩𝐚𝐭𝐢𝐚𝐥 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐄𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥𝐬 - 𝐒𝐞𝐜𝐨𝐧𝐝 𝐄𝐝𝐢𝐭𝐢𝐨𝐧 The book: https://lnkd.in/dy-7m_zz Sample: https://lnkd.in/dVP-Ty-Y GeoAI: https://lnkd.in/dDz_zgCH

🚀 Day 2 – Setting up the foundation Today was all about structuring the project properly. ⚙️ Work done: Created project in Replit Organized folders: src/ data/ pipelines/ Installed required Python libraries 💡 Lesson: A clean structure saves hours later when pipelines get complex. #DataEngineering #Python #Replit

Day 2 of learning Pandas Today was all about cleaning data handled missing values, dropped unnecessary columns, and did some basic filtering. Starting to see how messy data becomes usable with the right steps #Python #Pandas #DataScience #LearningJourney

Day 20 | Problem-Solving Practice Today I worked on determining the number of days in a given month and year. • Implemented a basic conditional approach • Optimized the solution using a set and simplified leap year logic Focused on handling edge cases like invalid month inputs and leap years correctly. Consistency over intensity — showing up every day and improving step by step. GitHub: https://lnkd.in/g35tV9Gj #ProblemSolving #Python #LearningInPublic #Consistency

🐍 Day2 of Python Learning Today, We explored: -What variables are and why they matter ✅ Numbers → int, float ✅ Text → str ✅ Boolean → True, False ✅ Using print() to display values It’s amazing how these simple concepts form the backbone of everything we build in Python. Every program starts with storing and manipulating data and today was a solid step toward that 💪 #Python #LearnPython #15DaysOfPython #Day2 #CodingJourney #Variables #DataTypes #PythonForBeginners #KeepLearning #GrowTogether

📘 Hypothesis testing (z-score) While learning hypothesis testing, the z-score was one concept I had to slow down for. At first, it looked like just a formula. But the idea is actually straightforward: A z-score tells you how far your result is from what you expected. It answers: “How unusual is this result?” Formula idea: (sample result − expected value) ÷ standard error What helped me understand it: Small z-score → result is normal Large z-score → result is unusual So instead of focusing on the formula, I started focusing on the meaning. That made it much easier to grasp. #DataScience #MeachineLearning #Python #LearningInPublic #DataCamp #DatacampAfrica

🚀 Day 3 — Python Journey Today’s focus was on float operations in Python (working with decimal numbers). 📌 What I learned: Float declaration Addition, subtraction, multiplication, division Rounding values using round() Scientific notation Precision handling in floats 💡 What I found interesting: Float values are not always 100% accurate due to precision limitations. Even simple calculations can sometimes give unexpected results. Understanding this early is important, especially for real-world applications like finance or data science. Step by step, trying to build a strong foundation. #Day3 #Python #CodingJourney #LearnInPublic #Consistency

Excited to share my latest blog on Getting Started with Matplotlib in Python! 📊 In this article, I’ve covered the basics of data visualization using Matplotlib and how we can turn raw data into meaningful insights. This project helped me strengthen my understanding of Python and data visualization concepts. 🔗 Read here: https://lnkd.in/g5HZZ4jt I’d love to hear your feedback! #Python #Matplotlib #DataVisualization #MediumBlog #LearningJourney

NaNs ruining your analysis? Here’s the quick Pandas trio: use isna() to detect missing values, dropna() to remove incomplete rows, and fillna() to replace gaps with defaults. This tiny example shows all three so you can clean data in seconds.#pandas #python #datascience #dataengineering

𝗗𝗮𝘆 𝟭 | 𝗦𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗺𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Today was my first step into Python, and I kept the focus on understanding the basics instead of trying to learn too many things at once. 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱: 💠 What Python is and why it is widely used, especially in data analysis Basic syntax and writing simple programs 💠 Understanding how Python executes code line by line I spent some time running small pieces of code just to get comfortable with the environment. Python feels quite readable, and that made the starting phase less overwhelming. Focusing on the basics at this stage is helping me build confidence for the topics ahead. #Python #DataAnalysis #LearningJourney #PythonBasics #Beginner #TechSkills