I would like to declare a column "InformationYetToEnter" in a data frame that concatenates variables I use under some conditions. I would like to start with it empty and do something based on whether it is still empty. Suppose I have the code down below. I concatenate values of variables, and if their resulting concatenation does not appear often enough, the row is erased.
I would like to declare the empty column as below with NA, however, the concatenation then returns something like NA 1 Good, not just 1 Good. How do I fix this?
How can I then check, whether the column is still empty during the algorithm, given that
Fruits<-Fruits %>% mutate(InformationYetToEnter = fct_lump_min(InformationYetToEnter, 2, other_level = "Too Rare")) %>% filter (InformationYetToEnter != "Too Rare")
returns an error if it is and, assuming I cannot use NA, is.na.data.frame() doesn't work anymore? NA's in the actual data should not be erased (as in checking for NA every iteration and deleting it before concatenation could run into a problem, when the first variable actually contains NA, which should not be deleted).
library(tidyverse) Fruit<-c("Banana", "Apple", "Banana", "Apple", "Apple") Origin<-c("New Guinea", "China","Germany", "USA", "Germany") Quality<-c("Good", "Bad", "Good", "Very bad", "Decent") Value<-c(50,75,80,60,30) #cents Price<-c(1,2,1,3,1) #euros InformationYetToEnter<-c(NA,NA,NA,NA,NA) Fruits<-data.frame(Fruit, Origin, Quality, Value, Price, InformationYetToEnter) Fruits$InformationYetToEnter<-paste(Fruits$InformationYetToEnter,Fruits$Price,Fruits$Quality) Fruits<-Fruits %>% mutate(InformationYetToEnter = fct_lump_min(InformationYetToEnter, 2, other_level = "Too Rare")) %>% filter (InformationYetToEnter != "Too Rare")