Hello Everyone,
Still new to R. Wrote some code that finds and prints invalid dates (see
below). This code works but I suspect it's not very good. If someone could show
me a better way, I'd greatly appreciate it.
Here is some information about what I'm trying to accomplish. My sense is that
the R date functions are best at identifying invalid dates when fed character
data in their default format. So my code converts the input dates to character,
breaks them apart using strsplit, and then reformats them. It then identifies
which dates are "missing" in the sense that the month or year are unknown and
prints out any remaining invalid date values.
As I see it, the code has at least 4 shortcomings.
1. It's too long. My understanding is that skilled programmers can usually or
often complete tasks like this in a few lines.
2. It's not vectorized. I started out trying to do something that was
vectorized but ran into problems with the strsplit function. I looked at the
help file and it appears this function will only accept a single character
vector.
3. It prints out the incorrect dates but doesn't indicate which date variable
they belong to. I tried various things with paste but never came up with
anything that worked. Ideally, I'd like to get something that looks roughly
like:
Error: Invalid date values in birthDT
"21931-11-23"
"1933-06-31"
Error: Invalid date values in diagnosisDT
"2010-02-30"
4. There's no way to specify names for input and output data. I imagine this
would be fairly easy to specify this in the arguments to a function but am not
sure how to incorporate it into a for loop.
Thanks,
Paul
##########################################
#### Code for detecting invalid dates ####
##########################################
#### Test Data ####
connection <- textConnection("
1 11/23/21931 05/23/2009 un/17/2011
2 06/20/1940 02/30/2010 03/17/2011
3 06/17/1935 12/20/2008 07/un/2011
4 05/31/1937 01/18/2007 04/30/2011
5 06/31/1933 05/16/2009 11/20/un
")
TestDates <- data.frame(scan(connection,
list(Patient=0, birthDT="", diagnosisDT="", metastaticDT="")))
close(connection)
TestDates
class(TestDates$birthDT)
class(TestDates$diagnosisDT)
class(TestDates$metastaticDT)
#### List of Date Variables ####
DateNames <- c("birthDT", "diagnosisDT", "metastaticDT")
#### Read Dates ####
for (i in seq(TestDates[DateNames])){
TestDates[DateNames][[i]] <- as.character(TestDates[DateNames][[i]])
TestDates$ParsedDT <- strsplit(TestDates[DateNames][[i]],"/")
TestDates$Month <- sapply(TestDates$ParsedDT,function(x)x[1])
TestDates$Day <- sapply(TestDates$ParsedDT,function(x)x[2])
TestDates$Year <- sapply(TestDates$ParsedDT,function(x)x[3])
TestDates$Day[TestDates$Day=="un"] <- "15"
TestDates[DateNames][[i]] <- with(TestDates, paste(Year, Month, Day, sep = "-"))
is.na( TestDates[DateNames][[i]] [TestDates$Month=="un"] ) <- T
is.na( TestDates[DateNames][[i]] [TestDates$Year=="un"] ) <- T
TestDates$Date <- as.Date(TestDates[DateNames][[i]], format="%Y-%m-%d")
TestDates$Invalid <- ifelse(is.na(TestDates$Date) &
!is.na(TestDates[DateNames][[i]]), 1, 0)
if( sum(TestDates$Invalid)==0 )
{ TestDates[DateNames][[i]] <- TestDates$Date } else
{ print ( TestDates[DateNames][[i]][TestDates$Invalid==1]) }
TestDates <- subset(TestDates, select = -c(ParsedDT, Month, Day, Year, Date,
Invalid))
}
TestDates
class(TestDates$birthDT)
class(TestDates$diagnosisDT)
class(TestDates$metastaticDT)
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