Following yesterday’s macro-level dive into industry trends,
today I zoomed in on a specific category that hits close to home:
치킨전문점 (Chicken Restaurants).

Why?
Because I used to run one — and I want to know which areas of Seoul would’ve made me rich (or bankrupt) 😅

🔍 What I explored today

1. Filtered the dataset to only include chicken restaurants
2. Grouped sales by 행정동 (administrative district)
   • Calculated: average sales, standard deviation, data count (number of quarters), and CV (coefficient of variation)
3. Sorted districts by total average sales
   • 역삼1동 and 종로1·2·3·4가동 top the list, with over ₩12 billion in yearly sales
4. Clarified that:
   • Sales values are per quarter, and
   • They represent the total revenue across all chicken shops in that district

🧠 Insights

• Some districts generate incredible volume — but that doesn’t mean every shop wins
• CV (변동계수) shows how stable or risky each location might be
• Realized I’d need store count data to estimate per-shop profitability

🔗 External Tool

Found a great external data source: 서울 골목상권 분석 서비스
It shows the number of registered businesses per district.
This will be essential for calculating “How much does the average shop make?”

🧩 Next Steps

• Manually collect chicken shop counts from the external source
• Merge with sales data to estimate revenue per store
• Use this to rank districts by potential profitability

Combining public data with real-world experience — this project’s finally becoming personal.