data/scripts/augment_meteo.R

   1 meteo_df = read.csv("meteo.csv")
   2
   3 #inspiration
   4 #http://stackoverflow.com/questions/8214303/conditional-replacement-of-values-in-a-data-frame
   5
   6 meteo_df$Season = 0
   7 meteo_df$Week = 0
   8 meteo_df$Pollution = -1
   9
  10 #Need to load and aggregate PM10 by days: use getData() from package
  11 ts_data = system.file("extdata","pm10_mesures_H_loc.csv",package="talweg")
  12 exo_data = system.file("extdata","meteo_extra_noNAs.csv",package="talweg")
  13 data = getData(ts_data, exo_data, input_tz = "Europe/Paris",
  14     working_tz="Europe/Paris", predict_at=0)
  15
  16 for (i in 1:nrow(meteo_df))
  17 {
  18     pm10_level = data$getLevel(i)
  19     #Fill Pollution column: -1 if no info, 0 to 2 for pollution level
  20     if (!is.nan(pm10_level))
  21     {
  22         if (pm10_level < 30)
  23             meteo_df$Pollution[i] = 0
  24         else if (pm10_level <= 50)
  25             meteo_df$Pollution[i] = 1
  26         else #pm10 > 50
  27             meteo_df$Pollution[i] = 2
  28     }
  29
  30     #Also fill season + days of week variables
  31     meteo_df$Season[i] = ifelse(
  32         strsplit(as.character(meteo_df$Date[i]),'/')[[1]][1] %in% c("4","5","6","7","8"),
  33         1, 0)
  34     current_datetime = strptime(as.character(meteo_df$Date[i]), "%m/%d/%Y", tz="GMT")
  35     meteo_df$Week[i] = ifelse(current_datetime$wday %in% c(6,0), 0, 1)
  36 }
  37
  38 #Finally write new data
  39 write.csv(meteo_df, file="meteo_extra.csv", row.names=FALSE)