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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