How to escape symbolic value in R I just loaded a csv file in R. When I ran the summary command for one of the columns, I got the following: 
> Error: unexpected symbol in "summary k_low"

I'm pretty sure I know what the 'unexpected symbol' is: for observations in which we had no reliable data for the variable k_low, we simply entered a period, or a . 
Is there a way to escape these observations in R? My boss uses STATA, which apparently escapes periods automatically, but I don't have STATA on my personal computer (and would prefer to use R in any case). 
So basically: Is there a way to get R to bypass any 'symbols' and return a summary of only those observations for which numerical data was entered? 
 A: It looks like you just left out the parentheses. Try
summary(k_low)

A: Looks like Rob got it right but I'll illustrate how to fix the period problem.
> testdata <- c(1, 2, 3, ".")
> testdata
[1] "1" "2" "3" "."
> summary(testdata)
   Length     Class      Mode 
        4 character character 
> #That's not what we want....
> cleandata <- as.numeric(testdata)
Warning message:
NAs introduced by coercion 
> cleandata
[1]  1  2  3 NA
> summary(cleandata)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
    1.0     1.5     2.0     2.0     2.5     3.0     1.0 

Notice that because the testdata vector had a period in it it converted everything to characters.  When we tell it to convert to numeric it doesn't know what to do with the periods so it automatically converts it to NA which is nice for what we want to do.  Then when you call summary on it it ignores the NAs for the summary but tells you how many NAs there are in the data.
A: When using read.table, read.csv or read.delim use:  
read.table(file,..., na.strings = ".", ...)

na.strings -    a character vector of strings which are to be interpreted as NA             values.
                Blank fields are also considered to be missing values in logical, 
                integer, numeric and complex fields.
A: Another point is that when you read in the data, it sound as if your "." is really a missing value.
So what you might wish to do when reading the data, is something like this:
k_low <- read.date(...,     na.strings = ".")
