Okay, so today I started digging for data.

I thought it’d be simple — go to some public data site, download a clean CSV with sales numbers, and boom: ready for EDA.

Turns out, nope.
Most “open” datasets are just business listings or metadata.
Like… I don’t need a list of coffee shops. I need to know how much coffee they sold.

I was about to give up, but then — jackpot.
I found this beautiful file from the Seoul Open Data platform with estimated monthly sales by business type.
Actual numbers. Per quarter. With breakdowns by day, gender, age group, even time of day.
Not perfect, but totally usable.

🧾 File I grabbed

• 서울시 상권분석서비스(추정매출-서울시).csv
• Contains:
  • total sales per month
  • weekday/weekend splits
  • daily patterns
  • gender & age-based transaction counts
  • and more goodies

I haven’t even opened it in pandas yet, but just reading the column names made me smile.

🧠 So what now?

I’m gonna take the night to look around for maybe 1 or 2 more datasets —
either to add as features or to cross-check this one.

Tomorrow I’ll open up Jupyter and get into the first real EDA notebook.
Excited to finally see what the data feels like when I mess with it.

This part’s always weirdly satisfying.

Stay tuned.