Re: [R] applying a set of rules to each row

Thu, 27 Jan 2011 10:03:36 -0800 


On Jan 27, 2011, at 8:45 AM, KATSCHKE, ADRIAN CIV DFAS wrote:


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 = ,
                               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
It's nice of Dennis to reorganize your logic, although if I sent you something privately I would expect it to remain private. An alternate approach to selecting a value based on a number falling into a range (bypassing the creation of a factor) is available using findInterval: 

multiplier <- c(55,30,60,20,65,5)[
findinterval(ageFedStart, c(0, 25, 30, 40, 45, 60, 100) ) ]
You are implicitly creating an index lookup into the initial vector of values. This is a very familiar operation to Excel users who often resort to VLOOKUP or HLOOKUP. Unlike cut, the default for findInterval is for the right side of the interval to be open which is the case here. 

--
David.
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
        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.
        


______________________________________________
R-help@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
West Hartford, CT

______________________________________________
R-help@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.

Reply via email to