Hello, I need to first apologize for the error in my first question dataframe$A = 20 dataframe$B = NA dataframe$A + dataframe$B actually returns NA
You quite understand my point of view. This is a household level data where you need to compute the total income of each household member before aggregating by household. Assume you have a household with 5 members 4 out of the 5 household members do have a full-time job 3 of the household members do not have a part-time job so that the column for these part-time job records NA for these three household members. 1 of the household members neither has a full-time nor part-time job When I add the column for the full-time job and the part-time job for the five household members, it returns NA as the total income for the two household members who at least should have their total income equal to their full-time job income. Based on the scenario described above, only one of the household members should have NA for the total income but R returns NA as the total income for the two household members who at least should have their total income equal to their full-time job income. This is just the first step because subsequently, I will need to compute mean. If I go ahead to replace the NA's with zeros it will bias my mean. So all I need is a way to still retain my NA so that my mean and other relevant computations will not be biased. Thank you -------------------------------------------- On Sun, 9/6/15, Rolf Turner <r.tur...@auckland.ac.nz> wrote: Subject: Re: [FORGED] [R] Handling "NA" in summation Date: Sunday, September 6, 2015, 7:16 PM On 07/09/15 10:22, Olu Ola via R-help wrote: > Hello, I am currently working with a dataframe which has some missing > values represented by "NA". whenever, I add two columns in which at > least one of the pair of an observation is "NA", the sum returns > zero. That is for the same observation, if > > dataframe$A = 20 dataframe$B = NA > > dataframe$A + dataframe$B returns zero. No it does not. It returns NA. As it should. > I do not want to delete the observations with the NA's. How do I go > about carrying out the necessary operations without deleting the > observations with the NA's. Your question seems to demonstrate a substantial amount of confusion. Amongst other things you probably want to deal with vectors (or perhaps matrices) rather than data frames. To sum a numeric vector, ignoring missing values, you can use the sum() function, setting the argument "na.rm" to TRUE. E.g. v <- c(1,NA,2,NA,3,NA,4,NA) sum(v,na.rm=TRUE) # Gives 10. Ignore other advice that you were given, to replace NAs in your data frame (???) by zeroes. That is very dangerous, misleading and confusing. "Missing" and "zero" are *VERY* different concepts. cheers, Rolf Turner -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276 ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
