Day 14 of my #DataAnalysiswithPython journey: I just completed the third project (Medical Data Visualizer) I wrangled health data and generated complex heatmaps and cat plots using Seaborn. Seeing those correlations come to life was exciting! Onto the next project .

Day 13 of my #DataAnalysisWithPython journey: Just completed my 2nd project in the FreeCodeCamp Data Analysis with Python course. I analyzed 1994 census demographic & income data using Pandas to uncover patterns and insights. Despite errors faced, I eventually got the output .

Day 12 of my #DataAnalysiswithPython journey I completed my first project — the Mean-Variance-Standard Deviation Calculator. It tested my understanding of NumPy, especially working with arrays and basic statistical calculations. Challenging, but I’m making steady progress.

Day 11 of my #DataAnalysisWithPython journey The structured learning phase is complete 🎉 Grateful for how far I’ve come—it hasn’t been easy. Wrapped up the final NumPy revision. Learning doesn’t end here—next up are the projects and earning my FreeCodeCamp certificate.

Day 10 of my #DataAnalysisWithPython journey Today I leveled up my Python skills—variables, loops, functions and more. Practiced pure Python logic with no extra libraries . Python really powers everything from calculations to data analysis! #Python #CodingJourney #freecodecamp

Day 9 of my #DataAnalysisWithPython journey : I Covered reading data from CSV/TXT files, databases, and parsing HTML with Pandas & Python. Also learned how to save data to various files types eg. Excel. after processing. Theory locked ,can't wait to apply it in a real project.

Day 8 of my #DataAnalysisWithPython journey: Became a data detective today! Cleaned a messy sales dataset from top to bottom,handled missing values, fixed dates, and polished text. The reward? Clean, insightful bar and line charts. See full cleanup in the video @freeCodeCamp

Day 7 of my #DataAnalysisWithPython journey: Data detective theory confirmed! I learnt the Pandas playbook for Data Cleaning: how to handle missing values, fix data types, and use .drop_duplicates(). I Can't wait to practice data cleaning and make visualizations on the data.

Day 6 of my #DataAnalysisWithPython journey :I Leveled up my Python skills in Google Colab using Pandas and Matplotlib. I analyzed student scores from a csv file, calculated totals/averages/grades, and visualized everything. The screen recording below shows the full process.

Day 5 of my #DataAnalysisWithPython journey Pandas felt like a new superpower today.I learned how Data Series and Frames work, loaded CSV files with "read_csv()", and even made my first simple plot with "plot()".Data just feels cleaner when Pandas takes over ! @freeCodeCamp

Day 4 of my #DataAnalysiswithPython journey: Today I leveled up my skills on @freecodecamp by practicing NumPy operations in Google Colab: ✅Array creation & mathematical functions ✅Boolean indexing & filtering ✅Statistical analysis on student data

Casual day in the office😊. Watch my latest tutorial on Exploratory Data Analysis with Pandas using this link youtu.be/GYiPEw-806M #DataAnalysis #DataScience #DataAnalysiswithPython @RxData_Hub

Day 3 of my #DataAnalysisWithPython journey Today was all about NumPy — one of the coolest tools I’ve touched so far. I learned how it handles numbers super fast, takes less memory than regular Python, and makes data feel alive in Jupyter Notebook. #DataAnalysis @freeCodeCamp

Day 2 of my #DataAnalysisWithPython journey Dived into Jupyter Notebook — learned how code & markdown cells work, how to import data, and some cool shortcuts. We used Notebook AI (like Google Colab). Feeling pumped to move on to NumPy & Pandas! #DataAnalysis @freeCodeCamp

#Day87 - #100DaysOfCode Commenced my #DataAnalysisWithPython Training on @freeCodeCamp. #Supercharged! ⚡⚡💪🏽