Is there any chance you meant
ddply (dat1 , .(Sector, FISCALYEAR), summarise, WROE=wavg(ROE, MKT))
??
It gives a result but I have no idea if it makes sense.
John Kane
Kingston ON Canada
> -----Original Message-----
> From: anandpu...@gmail.com
> Sent: Fri, 1 Mar 2013 14:13:37 -0500
> To: r-help@r-project.org
> Subject: Re: [R] Conditional Weighted Average (ddply or any other
> function)
>
> Hi John,
>
> The sample size is huge involving 10,000 + firms. I have put a
> representative sample using dput ( Name, ticker and country have been
> changed so that firms cannot be identified due to proprietary data
> set, also EPS is not required and removed from the dataset)
>
> structure(list(NAME = structure(c(8L, 8L, 8L, 8L, 8L, 8L, 7L,
> 7L, 7L, 7L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L,
> 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L,
> 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("CCC", "CTAX",
> "INN", "NOB", "SH", "SZ", "WASH", "WILLSON"), class = "factor"),
> Ticker = structure(c(7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L,
> 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L,
> 6L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L,
> 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("CC13",
> "CT56", "INN12", "NB12", "SH12", "SZ12", "W12", "W15"), class =
> "factor"),
> Industry = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L,
> 5L, 5L, 5L, 5L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Commercial &
> Professional Serv",
> "Energy", "Media", "Retail", "Transportation"), class = "factor"),
> Sector = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Consumer
> Discretionary",
> "Energy", "Industrials"), class = "factor"), Country =
> structure(c(4L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L), .Label = c("Brazil", "China", "India", "UK"), class =
> "factor"),
> FISCALYEAR = structure(c(3L, 2L, 1L, 4L, 5L, 6L, 3L, 2L,
> 1L, 4L, 5L, 6L, 3L, 2L, 1L, 4L, 5L, 6L, 3L, 3L, 2L, 1L, 4L,
> 5L, 6L, 3L, 2L, 1L, 4L, 5L, 6L, 3L, 2L, 1L, 4L, 5L, 6L, 3L,
> 2L, 1L, 4L, 5L, 6L, 3L, 2L, 1L, 4L, 5L, 6L), .Label = c("FY-1",
> "FY-2", "FY-3", "FY0", "FY1", "FY2"), class = "factor"),
> ROE = c(0.026, 0.0656, 0.1621, 0.1885, 0.1968, 0.2126, 0.0207,
> 0.0319, 0.0963, 0.0431, 0.066, 0.066, 0.0707, 0.0797, 0.0781,
> 0.078, 0.098, 0.126, 0.0352, 0.2625, 0.3714, 0.2929, 0.3133,
> 0.2509, 0.2398, 0.2779, 0.1109, 0.0509, 0.069, 0.1017, 0.1298,
> 0.5842, 0.3953, 0.4429, 0.3616, 0.26, 0.2, 0.4472, 0.2912,
> 0.21, 0.2849, 0.3553, 0.4347, 0.3289, 0.3846, 0.2643, 0.0458,
> 0.1265, 0.28), MKT = c(2919236084, 836858582, 2015182617,
> 3399344971, 4324821777, 4324821777, 7619453125, 3579844727,
> 4132238281, 3712239990, 2879757813, 2879757813, 1525237793,
> 700357605, 1814942993, 1858225342, 1242890503, 1242890503,
> 1879700000, 557093400, 224900300, 1634700000, 1443200000,
> 3582664735, 3582664735, 5830366211, 10660833984, 9024061523,
> 7628660645, 9154108398, 9154108398, 7064532227, 1804380005,
> 6331067871, 10445639648, 9153587891, 9153587891, 6231200000,
> 4.078e+09, 10107500000, 12460300000, 17800051556, 17800051556,
> 513478700, 260993500, 882575400, 1.151e+09, 855938413, 855938413
> )), .Names = c("NAME", "Ticker", "Industry", "Sector", "Country",
> "FISCALYEAR", "ROE", "MKT"), class = "data.frame", row.names = c(NA,
> -49L))
>
> Thanks,
> Punit
>
>> On Fri, Mar 1, 2013 at 12:51 PM, John Kane <jrkrid...@inbox.com> wrote:
>> See below
>>
>>
>>> -----Original Message-----
>>> From: anandpu...@gmail.com
>>> Sent: Fri, 1 Mar 2013 12:36:53 -0500
>>> To: jrkrid...@inbox.com
>>> Subject: Re: [R] Conditional Weighted Average (ddply or any other
>>> function)
>>>
>>> Hi John,
>>>
>>> I was using symbols, Column ROE, EPS, MKTCAP are numeric, Name,
>>> Ticker, Sector, Country, FISCALYEAR or Year are character strings.
>>>
>>> and column "Year" is referring to "FISCALYEAR"
>>>
>> Definitely a no-no in R-help. :) We really need some representative
>> sample data to play with. See
>> https://github.com/hadley/devtools/wiki/Reproducibility for some general
>> pointers on how to compose a good question. The fact that you included
>> the code you are using was excellent but without some data it is rather
>> useless.
>>
>> The easiest way to supply data is to use the dput() function. Example
>> with your file named "testfile":
>> dput(testfile)
>> Then copy the output and paste into your email. This is what I did with
>> your data that I pasted into my email . I added the dat1 <- to it.
>>
>> For large data sets, you can just supply a representative sample.
>> Usually, dput(head(testfile, 100)) will be sufficient.
>>
>> I hope this is of some help.
>>
>>
>>>
>>> On Fri, Mar 1, 2013 at 12:31 PM, John Kane <jrkrid...@inbox.com> wrote:
>>>> It is not at all clear what you are doing. You state that the data
>>>> set
>>>> you are using is what I have called dat1 : see dput form below.
>>>>
>>>> As far as I can see there is no numerical value in there.
>>>>
>>>> ##===========data set in dput form================#
>>>> dat1 <- structure(list(Name = c("N1", "N1", "N1", "N1", "N1", "N1",
>>>> "N1",
>>>> "N2", "N2", "N2", "N2", "N2", "N2", "N2"), Ticker = c("T1",
>>>> "T1",
>>>> "T1", "T1", "T1", "T1", "T1", "T2", "T2", "T2", "T2", "T2",
>>>> "T2",
>>>> "T2"), Sector = c("S1", "S1", "S1", "S1", "S1", "S1", "S1",
>>>> "S2",
>>>> "S2", "S2", "S2", "S2", "S2", "S2"), Industry = c("I1",
>>>> "I1",
>>>> "I1", "I1", "I1", "I1", "I1", "I2", "I2", "I2", "I2", "I2", "I2",
>>>> "I2"), Country = c("C1", "C1", "C1", "C1", "C1", "C1", "C1",
>>>> "C2", "C2", "C2", "C2", "C2", "C2", "C2"), Year = c("FY-4",
>>>> "FY-3",
>>>> "FY-2", "FY-1", "FY0", "FY1", "FY2", "FY-4", "FY-3", "FY-2",
>>>> "FY-2", "FY0", "FY2", "FY2"), ROE = c("ROE11", "ROE12",
>>>> "ROE13",
>>>> "ROE14", "ROE15", "ROE16", "ROE17", "ROE21", "ROE22",
>>>> "ROE23",
>>>> "ROE24", "ROE25", "ROE26", "ROE27"), EPS = c("EPS11",
>>>> "EPS12",
>>>> "EPS13", "EPS14", "EPS15", "EPS16", "EPS17", "EPS21",
>>>> "EPS22",
>>>> "EPS23", "EPS24", "EPS25", "EPS26", "EPS27"), MKTCAP =
>>>> c("MKT11",
>>>> "MKT12", "MKT13", "MKT14", "MKT15", "MKT16", "MKT17",
>>>> "MKT21",
>>>> "MKT22", "MKT23", "MKT24", "MKT25", "MKT26", "MKT27")),
>>>> .Names
>>>> = c("Name",
>>>> "Ticker", "Sector", "Industry", "Country", "Year", "ROE",
>>>> "EPS",
>>>> "MKTCAP"), class = "data.frame", row.names = c(NA, -14L))
>>>> ## =================end of dataset==================#
>>>>
>>>> There is no FISCALYEAR variable that you specifed below
>>>>
>>>>> ddply (dataread , .(Sector, FISCALYEAR), summarise, > WROE=wavg(ROE,
>>>>> MKTCAP)))
>>>>
>>>> I think we need a bit more information.
>>>>
>>>> John Kane
>>>> Kingston ON Canada
>>>>
>>>>
>>>>> -----Original Message-----
>>>>> From: anandpu...@gmail.com
>>>>> Sent: Fri, 1 Mar 2013 11:01:42 -0500
>>>>> To: r-help@r-project.org
>>>>> Subject: [R] Conditional Weighted Average (ddply or any other
>>>>> function)
>>>>>
>>>>> Hello R community,
>>>>>
>>>>> I am computing weighted average statistic by using ddply function:
>>>>>
>>>>> My data set is:
>>>>> N1 T1 S1 I1 C1 FY-4 ROE11 EPS11 MKT11
>>>>> N1 T1 S1 I1 C1 FY-3 ROE12 EPS12 MKT12
>>>>> N1 T1 S1 I1 C1 FY-2 ROE13 EPS13 MKT13
>>>>> N1 T1 S1 I1 C1 FY-1 ROE14 EPS14 MKT14
>>>>> N1 T1 S1 I1 C1 FY0 ROE15 EPS15 MKT15
>>>>> N1 T1 S1 I1 C1 FY1 ROE16 EPS16 MKT16
>>>>> N1 T1 S1 I1 C1 FY2 ROE17 EPS17 MKT17
>>>>> N2 T2 S2 I2 C2 FY-4 ROE21 EPS21 MKT21
>>>>> N2 T2 S2 I2 C2 FY-3 ROE22 EPS22 MKT22
>>>>> N2 T2 S2 I2 C2 FY-2 ROE23 EPS23 MKT23
>>>>> N2 T2 S2 I2 C2 FY-2 ROE24 EPS24 MKT24
>>>>> N2 T2 S2 I2 C2 FY0 ROE25 EPS25 MKT25
>>>>> N2 T2 S2 I2 C2 FY2 ROE26 EPS26 MKT26
>>>>> N2 T2 S2 I2 C2 FY2 ROE27 EPS27 MKT27
>>>>>
>>>>> with colnames:
>>>>> (Name,Ticker,Sector,Industry,Country,Year,ROE,EPS,MKTCAP)
>>>>>
>>>>> I want to compute
>>>>> 1) Weighted ROE based on Sector and Fiscal Year.
>>>>> For firm N1 of Sector S1 and Fiscalyear FY-3 weight is
>>>>> MKT1 / SUM(MKT, where Sector = S1, Fiscalyear FY-3)
>>>>>
>>>>> 2) Weighted ROE based on Country and Fiscal Year.
>>>>> For firm N1 of Country C1 and Fiscalyear FY-3 weight is
>>>>> MKT1 / SUM(MKT, where Country = C1, Fiscalyear FY-3)
>>>>>
>>>>> 3) Weighted ROE based on Country, Sector and Fiscal Year.
>>>>> For firm N1 of Country C1, Sector S1 and Fiscalyear FY-3
>>>>> weight is MKT1 / SUM(MKT, where Country = C1, Sector = S1, Fiscalyear
>>>>> FY-3)
>>>>>
>>>>> 4) Weighted ROE based on Country, Industry and Fiscal Year.
>>>>> For firm N1 of Country C1, Industry I1 and Fiscalyear FY-3
>>>>> weight is MKT1 / SUM(MKT, where Country = C1, Industry = I1,
>>>>> Fiscalyear
>>>>> FY-3)
>>>>>
>>>>>
>>>>> I tried using ddply function:
>>>>> ddply (dataread , .(Sector, FISCALYEAR), summarise, WROE=wavg(ROE,
>>>>> MKTCAP)))
>>>>>
>>>>> where wavg <- function(x, wt) x %*% wt/sum(wt)
>>>>> but this doesn't give me the right answer.
>>>>>
>>>>> I could try subseting the data into different sectors and compute the
>>>>> weighted average which doesn't look like an elegant solution and
>>>>> would
>>>>> defeat the purpose of ddply
>>>>>
>>>>> I coudn't think of properly using melt and cast functions to solve
>>>>> this issue. Any help will be highly appreciated.
>>>>>
>>>>> Thanks and Regards,
>>>>> Punit
>>>>>
>>>>> ______________________________________________
>>>>> 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.
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