Dennis,

This is excellent. Thank you for the help. I knew I had a tangle mess, but I 
didn't realize how much of a tangle until I used this code. The coding 
definitely simplified the process and sped up the execution time.

Adrian 
-----Original Message-----
From: Dennis Murphy [mailto:djmu...@gmail.com] 
Sent: Wednesday, January 26, 2011 4:57 PM
To: KATSCHKE, ADRIAN CIV DFAS
Subject: Re: [R] applying a set of rules to each row

Hi: 

I don't see the need for this labyrinth of if statements. Here's a way that I 
think solves the CSRS block with only one ifelse statement:

agefacC <- with(retireHelp, cut(ageFedStart, breaks = c(0, 25, 30, 40, 45, 60, 
100),
                                right = FALSE))
birthlevels <- c('[0,25)', '[30,40)', '[45,60)')
baseDate <- ifelse(agefacC %in% birthlevels, birthDT, serviceCompDT)
multiplier <- as.numeric( (agefacC == '[0,25)') * 55 +
                                       (agefacC == '[25,30)') * 30 +
                                       (agefacC == '[30,40)') * 60 +
                                       (agefacC == '[40,45)') * 20 +
                                       (agefacC == '[45,60)') * 65 +
                                       (agefacC == '[60,100)') * 5 )
rtDT <- baseDate + 365.25 * multiplier

I have no way of testing this on your data, but the idea is to use a vectorized 
approach to the problem rather than a series of conditional statements, which, 
as a CS type informed me recently, is the most time-consuming operation in 
computing. Double-check that this is an accurate restatement of your code.

Explanation of intent:
agefacC creates a factor from a continuous variable using the function cut(), 
with lower limit 0, upper limit 100 and intermediate breaks as given above. The 
argument right = FALSE closes the interval on the left instead of on the right.
> levels(agefacC)
[1] "[0,25)"   "[25,30)"  "[30,40)"  "[40,45)"  "[45,60)"  "[60,100)"

The birthlevels vector defines the age groups that use birthDT as the base 
date; the others use serviceCompDT. The ifelse statement (vectorized) uses 
birthDT as the base date (the constant term in rtDT) if the level of agefacC 
for each interval belongs to the levels in the vector birthlevels. If not, the 
base date is given by serviceCompDT.

The multiplier variable is the inner product of a logical statement 
corresponding to each level of agefacC times the multiplier of 365.25. 

Once these vectors are in place, rtDT is straightforward to compute in a 
vectorized fashion.

If this approach flies, you can modify the code for the other cases in a 
similar fashion. Hopefully, it not only simplifies the code, but also speeds up 
execution time.

HTH,
Dennis


On Wed, Jan 26, 2011 at 12:18 PM, KATSCHKE, ADRIAN CIV DFAS 
<adrian.katsc...@dfas.mil> wrote:


        All,
        
        I would like to apply a set of rules to each row of the sample data set
        below. The rule sets are the guidelines for determining an individual's
        date for retirement eligibility. The rules are found in this document,
        http://www.opm.gov/feddata/RetirementPaperFinal_v4.pdf. I am only
        interested in the top two categories for retirement eligibility, the
        CSRS and FERS plans.
        
        The data set has four variables Date of Birth (DOB), service computation
        date (srvCompDT), retirement plan (retirePlan), and the age at which the
        employee entered federal service (ageFedStart). The service computation
        date is used to compute the date eligible for retirement. The retirement
        plan indicates what system the employee is enrolled under.
        
        The data does contain a few other retirement plans, for now I want to
        just ignore those plans. I have labeled plans as 1-CSRS and 2-FERS, and
        3-Other. My first attempt at applying the rules was through a complex
        nesting of ifelse statements, this was not very successful and quite
        difficult to follow. I then wrote a function and tried using "apply"
        unsuccessfully. The function is shown below.
        
        I would like to put a short script or function together that would allow
        for an efficient application of the rules to each of the employees. I am
        trying to avoid a loop, because my data set is quite large, and I may
        need to update my data set regularly and re-run the analysis and reports
        that will come from this work.
        
        Any advice or guidance on building the function or code to apply the
        rules would be quite helpful.
        
        retireHelp <-
        structure(list(DOB = structure(c(-6642, -5134, -3444, -5598,
        -4356, 5737, -4894, -1951, -2950, 2467, 6945, 4908, -7930, -7236,
        -7727, -77, 4158, -7892, -6028, -7132, -5959, 2309, -2494, -3513,
        -383, -216, -3369, -5861, 3674, -10265, -8986, -5023, -4862,
        1526, -1022, 2175, -11790, -278, -7275, -5084, -1842, 430, -2220,
        -7444, 440, 4285, -7812, 3335, -7271, -6825, -1098, -1670, -10219,
        -7131, 5963, 704, -7662, 4219, -2813, 5147, -7334, -8223, -5922,
        -7497, -9276, -1291, -11640, -5631, 518, -7268, -2105, -5901,
        -690, -8146, -7059, 133, 1176, -6091, -2895, -6020, -4724, -3616,
        -5059, -8253, -2604, -12400, -4776, -3671, -9326, -7000, -5574,
        -3248, 4255, -1358, -6255, 8, -7115, -1701, -5227, 9, -517, -8674,
        -2554, -4069, -2077, -9872, -6534, 2970, -8307, -3020, -1343,
        -8897, -2304, -7424, 2078, -8274, -5559, -8888, -9262, -8473,
        -4088, -2429, -8006, -1091, 5015, 2765, 4036, 3101, -3743, 5103,
        -10018, -12095, -7646, -5966, -6208, -5784, -1325, -4288, -1665,
        -1409, 4685, -7881, -3413, 2738, -2201, 1217, -5113, 206, -1292,
        -1725, 10, -2978, -1895, -830, -105, -2395, -3496, -8244, -9956,
        -6494, -4678, -4077, 575, 2013, -3411, 3824, -4356, 4523, -5836,
        -6350, -5337, -41, -2001, -6632, -970, -6790, -2828, -4061, 476,
        5854, -9648, -4227, 850, 2619, -7747, -2672, 4069, -12618, -6898,
        -4178, -1772, -1643, -2064, -157, 4551, -8688, -6087, -2040,
        -7239, -783), format = "m/d/y", origin = structure(c(1, 1, 1970
        ), .Names = c("month", "day", "year")), class = c("dates", "times"
        )), srvCompDT = structure(c(743, 12429, 3585, 4364, 13227, 13578,
        13591, 8585, 9587, 13913, 14753, 13247, 2246, 1439, 8845, 7018,
        12625, -552, 5688, 7080, 13255, 13549, 12709, 13969, 13997, 9532,
        13689, 1226, 13549, 4093, 13423, 13801, 3181, 14809, 13353, 9457,
        7745, 8986, 4759, 4486, 6449, 11172, 8669, 3344, 13745, 12275,
        5081, 13605, 8006, 3048, 6330, 13521, 5254, 1733, 14095, 8516,
        4848, 13521, 5970, 14697, 8291, 139, 11435, 3567, 8961, 5775,
        3602, 1409, 11577, 12163, 12258, 13156, 9472, 7963, 1362, 10332,
        9557, 3997, 7509, 4691, 3133, 5877, 6782, 11449, 13283, 8040,
        11565, 3425, 7860, 1790, 10778, 13199, 12625, 5889, 3317, 9831,
        1068, 8040, 7123, 9104, 12836, 7928, 12764, 8922, 5324, -1004,
        1806, 10263, 5635, 10310, 5625, 8861, 14613, 3896, 10316, 5725,
        12751, 6113, 2997, 112, 5707, 4987, -1018, 8055, 13885, 13073,
        14585, 14865, 14935, 14390, 9735, 7654, 4557, 661, 1638, 1112,
        14011, 3086, 7032, 13942, 13325, 6735, 13900, 12673, 10148, 14193,
        14767, 8447, 6114, 10688, 13544, 7106, 8587, 14753, 7886, 12280,
        11946, 13662, 3332, 2108, 13977, 6203, 8369, 13857, 8369, 11486,
        8306, 12466, 12639, 7270, 4325, 13843, 14026, 14039, 6147, 7676,
        5781, 7038, 9187, 14640, 6174, 11491, 13913, 13787, 13465, 8854,
        13152, 1826, 1412, 4317, 5794, 5548, 8951, 12947, 12639, 5345,
        5961, 4637, 6465, 13717), format = "m/d/y", origin = structure(c(1,
        1, 1970), .Names = c("month", "day", "year")), class = c("dates",
        "times")), retirePlan = c(1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
        1, 3, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 1,
        2, 2, 2, 2, 3, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1,
        2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 3, 2, 1, 1, 2, 2, 2, 2, 2, 2, 1,
        3, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2,
        1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2,
        2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2,
        2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
        1, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,
        2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2),
           ageFedStart = c(20.22, 48.08, 19.24, 27.27, 48.14, 21.47,
           50.61, 28.85, 34.32, 31.34, 21.38, 22.83, 27.86, 23.75, 45.37,
           19.43, 23.18, 20.1, 32.08, 38.91, 52.61, 30.77, 41.62, 47.86,
           39.37, 26.69, 46.7, 19.4, 27.04, 39.31, 61.35, 51.54, 22.02,
           36.37, 39.36, 19.94, 53.48, 25.36, 32.95, 26.2, 22.7, 29.41,
           29.81, 29.54, 36.43, 21.88, 35.3, 28.12, 41.83, 27.03, 20.34,
           41.59, 42.36, 24.27, 22.26, 21.39, 34.25, 25.47, 24.05, 26.15,
           42.78, 22.89, 47.52, 30.29, 49.93, 19.35, 41.73, 19.27, 30.28,
           53.2, 39.32, 52.18, 27.82, 44.1, 23.06, 27.92, 22.95, 27.62,
           28.48, 29.33, 21.51, 25.99, 32.42, 53.94, 43.5, 55.96, 44.74,
           19.43, 47.05, 24.07, 44.77, 45.03, 22.92, 19.84, 26.21, 26.89,
           22.4, 26.67, 33.81, 24.9, 36.56, 45.45, 41.94, 35.57, 20.26,
           24.28, 22.83, 19.97, 38.17, 36.5, 19.08, 48.62, 46.32, 30.99,
           22.55, 38.33, 50.13, 41.07, 33.56, 23.5, 26.82, 20.3, 19.13,
           25.04, 24.28, 28.22, 28.88, 32.21, 51.14, 25.43, 54.08, 54.07,
           33.41, 18.14, 21.48, 18.88, 41.99, 20.19, 23.81, 42.03, 23.66,
           40.02, 47.4, 27.2, 33.81, 35.53, 54.43, 22.56, 20.28, 33.98,
           37.05, 27.61, 28.7, 42.66, 21.88, 40.18, 42.28, 59.98, 36.38,
           23.55, 51.07, 28.15, 21.34, 32.43, 32.25, 20.98, 34.67, 21.75,
           50.58, 37.29, 26.45, 38.01, 43.88, 56.59, 19.49, 39.61, 23.57,
           30.39, 23.85, 24.05, 43.32, 43.03, 35.76, 30.58, 58.08, 31.56,
           24.87, 39.55, 22.75, 23.26, 20.71, 19.69, 30.16, 35.88, 22.14,
           38.42, 32.99, 18.28, 37.52, 39.7)), .Names = c("DOB", "srvCompDT",
        "retirePlan", "ageFedStart"), row.names = c(NA, 200L), class =
        "data.frame")
        
        rrDT <- function(retSys, ageFedStart, birthDT, serviceCompDT){
           if(retSys == "CSRS") {
               if(ageFedStart < 25) rtDT <- dates(birthDT+(365.25*55))
               else if (ageFedStart >= 25 & ageFedStart < 30) rtDT <-
        dates(serviceCompDT+(365.25*30))
               else if (ageFedStart >= 30 & ageFedStart < 40) rtDT <-
        dates(birthDT+(365.25*60))
               else if (ageFedStart >= 40 & ageFedStart < 45) rtDT <-
        dates(serviceCompDT+(365.25*20))
               else if (ageFedStart >= 45 & ageFedStart < 60) rtDT <-
        dates(birthDT+(365.25*65))
               else if (ageFedStart >= 60) rtDT <-
        dates(serviceCompDT+(365.25*5))
               else rtDT <- NA
           }
           else if (retSys == "FERS") {
               if (birthDT < "01/01/53") {
                   if(ageFedStart < 25) rtDT <- dates(birthDT+(365.25*55))
                   else if (ageFedStart >= 25 & ageFedStart < 30) rtDT <-
        dates(serviceCompDT+(365.25*30))
                   else if (ageFedStart >= 30 & ageFedStart < 40) rtDT <-
        dates(birthDT+(365.25*60))
                   else if (ageFedStart >= 40 & ageFedStart < 42) rtDT <-
        dates(serviceCompDT+(365.25*20))
                   else if (ageFedStart >= 42 & ageFedStart < 57) rtDT <-
        dates(birthDT+(365.25*62))
                   else if (ageFedStart >= 57) rtDT <-
        dates(serviceCompDT+(365.25*5))
                   else rtDT <- NA
               }
               else if (birthDT >= "01/01/53" & birthDT < "01/01/70") {
                   if(ageFedStart < 26) rtDT <- dates(birthDT+(365.25*56))
                   else if (ageFedStart >= 27 & ageFedStart < 30) rtDT <-
        dates(serviceCompDT+(365.25*30))
                   else if (ageFedStart >= 30 & ageFedStart < 40) rtDT <-
        dates(birthDT+(365.25*60))
                   else if (ageFedStart >= 40 & ageFedStart < 42) rtDT <-
        dates(serviceCompDT+(365.25*20))
                   else if (ageFedStart >= 42 & ageFedStart < 57) rtDT <-
        dates(birthDT+(365.25*62))
                   else if (ageFedStart >= 57) rtDT <-
        dates(serviceCompDT+(365.25*5))
                   else rtDT <- NA
               }
               else if (birthDT >= "01/01/70"){
                   if(ageFedStart < 27) rtDT <- dates(birthDT+(365.25*56))
                   else if (ageFedStart >= 27 & ageFedStart < 30) rtDT <-
        dates(serviceCompDT+(365.25*30))
                   else if (ageFedStart >= 30 & ageFedStart < 40) rtDT <-
        dates(birthDT+(365.25*60))
                   else if (ageFedStart >= 40 & ageFedStart < 42) rtDT <-
        dates(serviceCompDT+(365.25*20))
                   else if (ageFedStart >= 42 & ageFedStart < 57) rtDT <-
        dates(birthDT+(365.25*62))
                   else if (ageFedStart >= 57) rtDT <-
        dates(serviceCompDT+(365.25*5))
                   else rtDT <- NA
               }
           }
           else rtDT <- NA
           return(rtDT)
        }
        
        Adrian R. Katschke
        Data Analytics Specialist
        Human Capital Program Office
        Human Resources
        PH: 317-212-7813
        DSN: 699-7813
        
        ______________________________________________
        R-help@r-project.org mailing list
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        PLEASE do read the posting guide 
http://www.R-project.org/posting-guide.html
        and provide commented, minimal, self-contained, reproducible code.
        


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