Stop R from converting a character factor to number - r

Question

I am trying to convert missing factor values to NA in a data frame, and create a new data frame with replaced values but when I try to do that, previously character factors are all converted to numbers. I cannot figure out what I am doing wrong and cannot find a similar question. Could anybody please help?
Here are my codes:
orders <- c('One','Two','Three', '')
ids <- c(1, 2, 3, 4)
values <- c(1.5, 100.6, 19.3, '')
df <- data.frame(orders, ids, values)
new.df <- as.data.frame(matrix( , ncol = ncol(df), nrow = 0))
names(new.df) <- names(df)
for(i in 1:nrow(df)){
row.df <- df[i, ]
print(row.df$orders) # "One", "Two", "Three", ""
print(str(row.df$orders)) # Factor
# Want to replace "orders" value in each row with NA if it is missing
row.df$orders <- ifelse(row.df$orders == "", NA, row.df$orders)
print(row.df$orders) # Converted to number
print(str(row.df$orders)) # int or logi
# Add the row with new value to the new data frame
new.df[nrow(new.df) + 1, ] <- row.df
}
and I get this:
> new.df
orders ids values
1 2 1 2
2 4 2 3
3 3 3 4
4 NA 4 1
but I want this:
> new.df
orders ids values
1 One 1 1.5
2 Two 2 100.6
3 Three 3 19.3
4 NA 4

Answer 1

Convert empty values to NA and use type.convert to change their class.
df[df == ''] <- NA
df <- type.convert(df)
df
# orders ids values
#1 One 1 1.5
#2 Two 2 100.6
#3 Three 3 19.3
#4 <NA> 4 NA
str(df)
#'data.frame': 4 obs. of 3 variables:
#$ orders: Factor w/ 4 levels "","One","Three",..: 2 4 3 1
#$ ids : int 1 2 3 4
#$ values: num 1.5 100.6 19.3 NA

Answer 2

Thanks to the hint from Ronak Shah, I did this and it gave me what I wanted.
df$orders[df$orders == ''] <- NA
This will give me:
> df
orders ids values
1 One 1 1.5
2 Two 2 100.6
3 Three 3 19.3
4 <NA> 4
> str(df)
'data.frame': 4 obs. of 3 variables:
$ orders: Factor w/ 4 levels "","One","Three",..: 2 4 3 NA
$ ids : num 1 2 3 4
$ values: Factor w/ 4 levels "","1.5","100.6",..: 2 3 4 1
In case you are curious about the difference between NA and as I was, you can find the answer here.
Your suggestion
df$orders[is.na(df$orders)] <- NA
did not work maybe becasuse missing entry is not NA?