Post by Aashita Mishra

Day 20 🚀 Built a mini project focused on transforming messy sales data into a clean, analysis-ready dataset — closer to real-world data engineering work. Handled missing values smartly: Used median imputation for the amount column to avoid skew from outliers Checked null patterns using isnull() to understand data gaps. Cleaned date-time inconsistencies: Standardized formats using datetime conversion Ensured proper sorting & usability for time-based analysis Detected & removed outliers Applied logical filtering and basic statistical checks. Improved text formatting: Fixed casing, spacing, and inconsistencies Made dataset clean and structured Applied a data validation mindset Verified consistency across columns Ensured no unintended data loss during cleaning Outcome. Messy sales data ➝ clean, reliable, and ready for analysis or dashboarding 📊 Special thanks to Anurag Srivastava 🙌 for guidance and support throughout the learning journey.