Pandas Selecting, Filtering & Transforming Data | Data Science Day 5

How do you find exactly the rows you need inside a large dataset? In Day 5 of our 15-Day Beginner Data Science Sprint, we learn how to ask precise questions of a table using Pandas. In this beginner-friendly lesson, you will learn how to: ✅ Select one or multiple columns ✅ Select rows using .loc[] and .iloc[] ✅ Filter data using one or multiple conditions ✅ Use & for AND and | for OR ✅ Sort values from highest to lowest ✅ Rename columns ✅ Create derived columns such as improvement and performance bands ✅ Use .copy() to safely transform filtered data We will work with a student-performance dataset and answer questions such as: Which students have low attendance and low scores? Which students studied for more than three hours but still scored below 60? Which students improved the most? Which students have attendance above 85 and scores above 80? By the end of this lesson, you will be able to extract useful information from a DataFrame instead of manually reading every row. 📓 Notebook: Day_05_Selecting_Filtering_and_Transforming_Data.ipynb This series is designed for complete beginners. Follow all 15 days to understand the complete data science workflow and build your first machine learning project using Python. Core stack: Google Colab, Python, NumPy, Pandas, Seaborn and scikit-learn. #DataScience #Python #Pandas #DataAnalysis #MachineLearning #GoogleColab #LearnPython #DataScienceForBeginners