--- /dev/null
+meteo_df = read.csv("meteo.csv")
+
+meteo_df$Season = 0
+meteo_df$Week = 0
+meteo_df$Pollution = -1
+
+#Need to load and aggregate PM10 by days
+pm10_df = read.csv("pm10_mesures.csv")
+
+line_number = 1 #line number in pm10 file
+for (i in 1:(nrow(meteo_df)))
+{
+ pm10s = c()
+ repeat {
+ {
+ pm10s = c(pm10s, pm10_df[line_number,2])
+ line_number = line_number + 1
+ };
+ if (line_number >= nrow(pm10_df)+1
+ || strsplit(as.character(pm10_df[line_number,1])," ")[[1]][2] == '0:15')
+ {
+ break
+ }}
+ pm10_level = mean(pm10s, na.rm=TRUE)
+ #Fill Pollution column: -1 if no info, 0 to 2 for pollution level
+ if (!is.nan(pm10_level))
+ {
+ if (pm10_level < 30)
+ meteo_df$Pollution[i] = 0
+ else if (pm10_level <= 50)
+ meteo_df$Pollution[i] = 1
+ else #pm10 > 50
+ meteo_df$Pollution[i] = 2
+ }
+
+ #Also fill season + days of week variables
+ meteo_df$Season[i] = ifelse(
+ strsplit(as.character(meteo_df$Date[i]),'/')[[1]][1] %in% c("4","5","6","7","8"),
+ 1, 0)
+ current_datetime = strptime(as.character(meteo_df$Date[i]), "%m/%d/%Y", tz="GMT")
+ meteo_df$Week[i] = ifelse(current_datetime$wday %in% c(6,0), 0, 1)
+}
+
+#see also:
+#http://stackoverflow.com/questions/8214303/conditional-replacement-of-values-in-a-data-frame
+
+#Finally write new data
+write.csv(meteo_df, file="meteo_extra.csv", row.names=FALSE)