Delete rows with blank values in one particular column

Question

I am working on a large dataset, with some rows with NAs and others with blanks:

df <- data.frame(ID = c(1:7),                                             home_pc = c("","CB4 2DT", "NE5 7TH", "BY5 8IB", "DH4 6PB","MP9 7GH","KN4 5GH"),                         start_pc = c(NA,"Home", "FC5 7YH","Home", "CB3 5TH", "BV6 5PB",NA),                         end_pc = c(NA,"CB5 4FG","Home","","Home","",NA)) 

How do I remove the NAs and blanks in one go (in the start_pc and end_pc columns)? I have in the past used:

df<- df[-which(is.na(df$start_pc)), ] 

... to remove the NAs - is there a similar command to remove the blanks?

Answer 1

 df[!(is.na(df$start_pc) | df$start_pc==""), ] 

Answer 2

It is the same construct - simply test for empty strings rather than NA:

Try this:

df <- df[-which(df$start_pc == ""), ] 

In fact, looking at your code, you don't need the which, but use the negation instead, so you can simplify it to:

df <- df[!(df$start_pc == ""), ] df <- df[!is.na(df$start_pc), ] 

And, of course, you can combine these two statements as follows:

df <- df[!(df$start_pc == "" | is.na(df$start_pc)), ] 

And simplify it even further with with:

df <- with(df, df[!(start_pc == "" | is.na(start_pc)), ]) 

You can also test for non-zero string length using nzchar.

df <- with(df, df[!(nzchar(start_pc) | is.na(start_pc)), ]) 

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Disclaimer: I didn't test any of this code. Please let me know if there are syntax errors anywhere