1️⃣ Examined 50,000+ customer records on Zomato, focusing on 17 factors such as ratings and costs, utilizing Python, Pandas, and data visualization. Pinpointed prime locations, popular cuisines, and lucrative customer segments. 2️⃣ Enhanced accuracy by 20% to predict profitable locations through detailed analysis and data cleaning, addressing issues like missing values and duplicates. 3️⃣ Identified top 10 sought-after locations and budget-friendly choices for couples by employing grouping, sorting, and statistical analysis. 4️⃣ Visualized key correlations like cost vs ratings to inform expansion strategies.