# [R] applying a set of rules to each row

Thu Jan 27 14:45:23 CET 2011

```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.

-----Original Message-----
From: Dennis Murphy [mailto:djmuser at gmail.com]
Sent: Wednesday, January 26, 2011 4:57 PM
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.KATSCHKE at 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

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)
}

Data Analytics Specialist
Human Capital Program Office
Human Resources
PH: 317-212-7813
DSN: 699-7813

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