[R] Conditional Weighted Average (ddply or any other function)

[John Kane]

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: anandpunit at gmail.com
> Sent: Fri, 1 Mar 2013 11:01:42 -0500
> To: r-help at 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
> 
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> and provide commented, minimal, self-contained, reproducible code.

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