I use read.csv to read two different sets of data: rawdata1 and rawdata2. rawdata 1 always exists while rawdata2 may not be available.
rawdata1 <- read.csv(file=rawdata1.csv)
rawdata2 <- read.csv(file=rawdata2.csv)
Each .csv has two columns with data (date is matching):
date value
What I want to do: In case there is a rawdata2.csv available, I want to create a new table "rawdata" by joining rawdata1 and rawdata2 by "date" (I manage to do that). If not, I want to create "rawdata" by assigning rawdata1 to it and adding a new column with value 0 (to represent the missing data for rawdata2, which is 0 if missing). I think I need this column because calculations depend on both values.
How I tried to do it:
if(exists("rawdata2")) {
rawdata <- left_join(rawdata1,rawdata2,by = "date")
} else {
rawdata <- rawdata1 %>%
rawdata$value_2 <- 0
}
Error:
Error in rawdata_bezug %>% rawdata$Zaehlerstand_abgabe <- 0 :
could not find function "%>%<-"
Doing it with dplyr/tidyr doesn't seem to work, but I couldn't find another solution so far.
Thanks for the help :)
Aucun commentaire:
Enregistrer un commentaire