Eliminating Existing Observations in a Zoo Merge

Question

I'm trying to do a zoo merge between stock prices from selected trading days and observations about those same stocks (we call these "Nx observations") made on the same days. Sometimes do not have Nx observations on stock trading days and sometimes we have Nx observations on non-trading days. We want to place an "NA" where we do not have any Nx observations on trading days but eliminate Nx observations where we have them on non-trading day since without trading data for the same day, Nx observations are useless.

The following SO question is close to mine, but I would characterize that question as REPLACING missing data, whereas my objective is to truly eliminate observations made on non-trading days (if necessary, we can change the process by which Nx observations are taken, but it would be a much less expensive solution to leave it alone).

merge data frames to eliminate missing observations

The script I have prepared to illustrate follows (I'm new to R and SO; all suggestions welcome):

# create Stk_data data.frame for use in the Stack Overflow question
Date_Stk <- c("1/2/13", "1/3/13", "1/4/13", "1/7/13", "1/8/13") # dates for stock prices used in the example
ABC_Stk <- c(65.73, 66.85, 66.92, 66.60, 66.07) # stock prices for tkr ABC for Jan 1 2013 through Jan 8 2013
DEF_Stk <- c(42.98, 42.92, 43.47, 43.16, 43.71) # stock prices for tkr DEF for Jan 1 2013 through Jan 8 2013
GHI_Stk <- c(32.18, 31.73, 32.43, 32.13, 32.18) # stock prices for tkr GHI for Jan 1 2013 through Jan 8 2013
Stk_data <- data.frame(Date_Stk, ABC_Stk, DEF_Stk, GHI_Stk) # create the stock price data.frame

# create Nx_data data.frame for use in the Stack Overflow question
Date_Nx <- c("1/2/13", "1/4/13", "1/5/13", "1/6/13", "1/7/13", "1/8/13") # dates for Nx Observations used in the example
ABC_Nx <- c(51.42857, 51.67565, 57.61905, 57.78349, 58.57143, 58.99564) # Nx scores for stock ABC for Jan 1 2013 through Jan 8 2013
DEF_Nx <- c(35.23809, 36.66667, 28.57142, 28.51778, 27.23150, 26.94331) # Nx scores for stock DEF for Jan 1 2013 through Jan 8 2013
GHI_Nx <- c(7.14256, 8.44573, 6.25344, 6.00423, 5.99239, 6.10034) # Nx scores for stock GHI for Jan 1 2013 through Jan 8 2013
Nx_data <- data.frame(Date_Nx, ABC_Nx, DEF_Nx, GHI_Nx) # create the Nx scores data.frame

# create zoo objects & merge
z.Stk_data <- zoo(Stk_data, as.Date(as.character(Stk_data[, 1]), format = "%m/%d/%Y"))
z.Nx_data <- zoo(Nx_data, as.Date(as.character(Nx_data[, 1]), format = "%m/%d/%Y"))
z.data.outer <- merge(z.Stk_data, z.Nx_data)

The NAs on Jan 3 2013 for the Nx observations are fine (we'll use the na.locf) but we need to eliminate the Nx observations that appear on Jan 5 and 6 as well as the associated NAs in the Stock price section of the zoo objects.

I've read the R Documentation for merge.zoo regarding the use of "all": that its use "allows intersection, union and left and right joins to be expressed". But trying all combinations of the following use of "all" yielded the same results (as to why would be a secondary question).

z.data.outer <- zoo(merge(x = Stk_data, y = Nx_data, all.x = FALSE)) # try using "all"

While I would appreciate comments on the secondary question, I'm primarily interested in learning how to eliminate the extraneous Nx observations on days when there is no trading of stocks. Thanks. (And thanks in general to the community for all the great explanations of R!)

Answer 1

The all argument of merge.zoo must be (quoting from the help file):

logical vector having the same length as the number of "zoo" objects to be merged 
(otherwise expanded)

and you want to keep all rows from the first argument but not the second so its value should be c(TRUE, FALSE).

merge(z.Stk_data, z.Nx_data, all = c(TRUE, FALSE))

The reason for the change in all syntax for merge.zoo relative to merge.data.frame is that merge.zoo can merge any number of arguments whereas merge.data.frame only handles two so the syntax had to be extended to handle that.

Also note that %Y should have been %y in the question's code.

Answer 2

I hope I have understood your desired output correctly ("NAs on Jan 3 2013 for the Nx observations are fine"; "eliminate [...] observations that appear on Jan 5 and 6"). I don't quite see the need for zoo in the merging step.

merge(Stk_data, Nx_data, by.x = "Date_Stk", by.y = "Date_Nx", all.x = TRUE)

#   Date_Stk ABC_Stk DEF_Stk GHI_Stk   ABC_Nx   DEF_Nx  GHI_Nx
# 1   1/2/13   65.73   42.98   32.18 51.42857 35.23809 7.14256
# 2   1/3/13   66.85   42.92   31.73       NA       NA      NA
# 3   1/4/13   66.92   43.47   32.43 51.67565 36.66667 8.44573
# 4   1/7/13   66.60   43.16   32.13 58.57143 27.23150 5.99239
# 5   1/8/13   66.07   43.71   32.18 58.99564 26.94331 6.10034