| 12345678910111213141516171819202122232425262728 |
- # RF temperature modeling
- #
- # Read in data
- library(tidyverse)
- library(lubridate)
- temps <- read_csv('1159640.csv')
- temps <- mutate(temps, month = lubridate::month(DATE),
- day = lubridate::day(DATE), week = lubridate::wday(DATE, label = TRUE))
- temps$temp_1 <- c(45, temps$TMAX[1:{nrow(temps) - 1}])
- temps$temp_2 <- c(45, 44, temps$TMAX[1:{nrow(temps) - 2}])
- averages <- read_csv('1159653.csv')
- averages <- dplyr::filter(averages, STATION_NAME == 'SEATTLE TACOMA INTERNATIONAL AIRPORT WA US')
- averages$month <- as.numeric(substr(averages$DATE, 5, 6))
- averages$day <- as.numeric(substr(averages$DATE, 7, 8))
- temps <- merge(temps, averages[, c('month', 'day', 'DLY-TMAX-NORMAL')], by = c('month', 'day'),
- all.x = TRUE)
- temps <- temps[, c('month', 'week', 'day', 'DATE', 'TMAX', 'temp_1', 'temp_2', 'DLY-TMAX-NORMAL')]
- temps <- dplyr::rename(temps, date = DATE, actual = TMAX)
- temps <- dplyr::rename(temps, average = 'DLY-TMAX-NORMAL')
- temps$year <- 2016
- temps <- temps[, -which(names(temps) == 'date')]
- write_csv(temps, 'mod_temps.csv')
|
