demand_1year_hourly<-ggplot(data=demand_1year_hourly_v2, aes(x=Date_Time, y=Demand_kW, color=Types))+

Demand kW: Actual vs Predicted Demand - Hourly, 1year data - limits=c(1000kW, 2500kW)

Tidycensus, Tigris 패키지 활용

How it starts: This pet project started from a desire to track what my daughter’s doctors were prescribing her. My daughter Hayoon spent most of her days in daycare and would often end up catching various viruses or developing skin issues. Sometimes she needed to visit the doctor once or twice each week. In Korea, it is incredibly easy to and convenient to visit any doctor or clinic of your choice, but there is never enough time to deeply consult with medical professionals concerning the health issues that brought you in for their care. Each time we left the doctor’s office with a new prescription and I began to wonder exactly what kind of medicine was being prescribed. Even though I asked the doctors to share my daughter’s EMR data with me, I could not get them to share a digital version, so I needed to collect all of her paper prescriptions and type them into a spreadsheet by hand.

하윤의 2019년 소아과 처방전 데이터 EDA