Comparing dates in dataframes
But, but, but .... there is no weather goodness variable in weather?!?!?! > str(weather) 'data.frame': 155 obs. of 4 variables: $ Date :Class 'Date' num [1:155] 14245 14245 14245 14245 14245 ... $ minute : int 5 15 30 45 0 15 30 45 0 15 ... $ hour : int 15 15 15 15 17 17 17 17 18 18 ... $ quarter: int 65 75 90 105 68 83 98 113 72 87 .. I thought you said the "weather" dataframe would have some information about "goodness" that we were supposed to map to arrivals.? What is the meaning of those variables? How do we define a "good" quarter hour? And why are the values of quarter not 1, 2, 3, 4? They ought to be a factor or integer that could be matched to those that are in "arr", which are also apparently not so defined. Let's see a better codebook or description of these variables.
On Jan 17, 2010, at 6:47 PM, James Rome wrote:
Here are some sample data sets. I also tried making a combined field in each set such as adq=paste(as.character(arr$Date), as.character(arr$quarter)) and similarly for the weather set, so I have unique single things to compare, but that did not seem to help much. Thanks, Jim On 1/17/10 5:50 PM, David Winsemius wrote:
My guess (since we still have no data on which to test these ideas) is that you need either to merge() or to use a matrix created from the dates and qtr-hours entries in "gw", since matching on dates and hours separately will not uniquely classify the good qtr-hours within their proper corresponding dates. You want a structure (or a matching process) that takes: hqhr1 qhr2 qhr3 qhr4 ....... date1 good bad good bad date2 bad good good good date3 bad bad bad good . . . and lets you use the values in "arr" to get values in "gw". Notice that the notion of arr$Date %in% gw$date & arr$qtrhr %in% gw$qtrhr simply will not accomplish anything correct/ Merging by multiple criteria (with the merge function) would do that or you could construct a matrix whose entries were the categories good /bad. The table function could create the matrix for the purpose of using an indexed solution if you are dead-set against the merge concept. On Jan 17, 2010, at 4:47 PM, James Rome wrote:
Thank you Dennis. arr$gw <- as.numeric(weather$Date == arr$Date & arr$quarter %in% weather$quarter) seems to be what I want to do, but in fact, with the full data set, it misidentifies the rows, so I think the error message must mean something.
arrr$Date <- as.Date(as.character(ewr$Date),format="%m/%d/%y") weather$Date <- as.Date(as.character(weather$Date),format="%m/%d/ %y") gw = c(length(arrr)) gw[1:length(arrr[,1])]=FALSE gw[arrr$Date==weather$Date & weather$quarter %in% arr$quarter]
Warning in `==.default`(arr$Date, weather$Date) : longer object length is not a multiple of shorter object length Warning in arr$Date == weather$Date & weather$quarter %in% arr $quarter : longer object length is not a multiple of shorter object length [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [223] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [260] 0 0 0 0 0 0 0 0 There are many many more matches in the 99k line arrival data set. Thanks a bunch, Jim On 1/17/10 3:21 PM, Dennis Murphy wrote:
Hi:
To read a data set from a R-help message into R, one uses
read.table(textConnection("<verbatim text>"), ...)
Your weather data set had
(a) a variable name with a space in it, that R misread and had to
be
altered manually;
(b) a missing value with no NA that R interpreted as an incomplete
line; again, it had
to be altered manually.
This is why David suggested the use of dput(), so that these
vagaries
don't have to be
dealt with by those who are trying to help.
That being said, for the example that you gave and the desired
value
that you wanted, try
arr$gw <- as.numeric(weather$Date == arr$Date & arr$quarter %in%
weather$quarter)
(I changed DateTime to Date in the arr data frame...)
You'll get warnings like
Warning messages:
1: In is.na <http://is.na>(e1) | is.na <http://is.na>(e2) :
longer object length is not a multiple of shorter object length
but it seems to do the right thing. The first equality is there to
constrain matches for
quarter to be within the same day.
For future reference,
dput(weather)
structure(list(Date = structure(c(1L, 1L, 1L, 1L), .Label =
"1/1/09",
class = "factor"),
minute = c(5L, 15L, 30L, 45L), hour = c(15L, 15L, 15L, 15L
), quarter = 60:63, efficiency = c(NA, 72, 63.3, 85.4)), .Names =
c("Date",
"minute", "hour", "quarter", "efficiency"), class = "data.frame",
row.names = c(NA,
-4L))
dput(arr)
structure(list(Date = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "1/1/09",
class = "factor"),
weekday = c(5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L), month = c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L),
quarter = c(59L, 59L, 60L, 60L, 60L, 60L, 60L, 60L, 60L,
60L, 60L, 60L, 60L, 61L, 61L, 61L, 61L, 66L, 67L), ICAO =
structure(c(6L,
8L, 7L, 3L, 6L, 3L, 5L, 3L, 3L, 1L, 3L, 5L, 3L, 3L, 6L, 6L,
2L, 4L, 3L), .Label = c("AAL", "AWE", "BTA", "CHQ", "CJC",
"COA", "JBU", "NWA"), class = "factor"), Flight =
structure(c(15L,
19L, 18L, 6L, 17L, 8L, 12L, 5L, 4L, 1L, 3L, 13L, 9L, 10L,
14L, 16L, 2L, 11L, 7L), .Label = c("AAL842", "AWE307", "BTA1234",
"BTA2064", "BTA2085", "BTA2347", "BTA2405", "BTA2916", "BTA3072",
"BTA3086", "CHQ5312", "CJC3225", "CJC3359", "COA1166", "COA349",
"COA855", "COA886", "JBU554", "NWA9934"), class = "factor"),
gw = c(FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE,
FALSE)), .Names = c("Date", "weekday", "month", "quarter",
"ICAO", "Flight", "gw"), row.names = c(NA, -19L), class =
"data.frame")
These can be copied and pasted directly into an R session without
modification.
HTH,
Dennis
On Sun, Jan 17, 2010 at 10:51 AM, James Rome <jamesrome at gmail.com
<mailto:jamesrome at gmail.com>> wrote:
On 1/17/10 1:06 PM, David Winsemius wrote:
On Jan 17, 2010, at 12:37 PM, James Rome wrote:
I don't think it is that simple because it is not a one-to-one
match. In
the arr data frame, there are many arrivals in a quarter hour
with good
weather on a given day. So I need to match the date and the quarter hour. And all of the rows in the weather data frame are times with good weather--unique date + quarter hour. That is why I needed the
loop. For
each date and quarter hour in weather, I want to mark all the
entries
with the corresponding date and weather as TRUE in the arr$gw
column.
I did convert the dates to POSIXlt dates and rewrote my
function as
gooddates = function(all, good) {
la = length(all) # All the arrivals
lw = length(good) # The good 15-minute periods
for(j in 1:lw) {
d=good$Date[j]
q=good$quarter[j]
all$gw[all$Date==d && all$quarter==q]=TRUE
You are attempting a vectorized test and assignment with "&&" which seems unlikely to succeed, but even then I am not sure your problems would be over. (I'm also guessing that you might not have reported a warning.)
Why shouldn't the && succeed? You are correct there, because I do get items if I use either part of this and test, when I insert the &&, I get no hits. And I got no warnings.
Why not merge arr to gw by date and quarter?
The sets contain different data, and the only thing I want from the weather set is the fact that it has an entry for a given date and time
Answering these questions would be greatly speeded up with a small sample dataset. Are you aware of the virtues of the dput function?
What I want is for a 1 to be in the gw column in the quarter
60,61,62,63,...
For example, here is some data from the good weather set:
Date minute hour quarter Efficiency Val
1/1/09 5 15 60
1/1/09 15 15 61 72
1/1/09 30 15 62 63.3
1/1/09 45 15 63 85.4
And this is from the arrivals set:
DateTime weekday month quarter ICAO
Flight gw
1/1/09 5 1 59 COA COA349 0
1/1/09 5 1 59 NWA NWA9934 0
1/1/09 5 1 60 JBU JBU554 0
1/1/09 5 1 60 BTA BTA2347 0
1/1/09 5 1 60 COA COA886 0
1/1/09 5 1 60 BTA BTA2916 0
1/1/09 5 1 60 CJC CJC3225 0
1/1/09 5 1 60 BTA BTA2085 0
1/1/09 5 1 60 BTA BTA2064 0
1/1/09 5 1 60 AAL AAL842 0
1/1/09 5 1 60 BTA BTA1234 0
1/1/09 5 1 60 CJC CJC3359 0
1/1/09 5 1 60 BTA BTA3072 0
1/1/09 5 1 61 BTA BTA3086 0
1/1/09 5 1 61 COA COA1166 0
1/1/09 5 1 61 COA COA855 0
1/1/09 5 1 61 AWE AWE307 0
1/1/09 5 1 66 CHQ CHQ5312 0
1/1/09 5 1 67 BTA BTA2405 0
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______________________________________________ R-help at r-project.org mailing list 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.
David Winsemius, MD Heritage Laboratories West Hartford, CT
<arr.rda><weather.rda>
David Winsemius, MD Heritage Laboratories West Hartford, CT