I have to agree with Daniel Nordlund regarding not creating subsidiary
problems when the main problem has been cracked. Nonetheless, ...
might you be happier with the result of changing the last data.frame()
call in calcProfit to c()?
I get a matrix:
> str(Results2)
num [1:14, 1:16] 3.00e+04 3.00 -4.50e+02 -1.50e-02 -1.54e-02
7.50e-01 -5.00e-01 1.00e+04 -1.50e-02 2.00e-04 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:14] "OutTotInvestment" "OutNumInvestments.investment"
"OutDolProf" "OutPerProf" ...
..$ : NULL
... if you go along with that strategy, then I think it is possible
that you really want as.data.frame( t( Results2)) since the rows and
columns seem to be transposed from what I would have wanted.
Now, ... your next task is to set up your mail-client so it sends
unformatted text to R-help.
--
David Winsemius
Heritage Labs
On Dec 23, 2008, at 11:36 AM, Brigid Mooney wrote:
------------------------------------------------------------------------------------------------------------------------------
Problem Description: (reproducible code below)
------------------------------------------------------------------------------------------------------------------------------
I cannot seem to get as.data.frame() to work as I would expect.
Results2 seems to contain repeated column titles for each row, as
well as a row name 'investment' (which is not intended), like:
Results2
[[1]]
OutTotInvestment OutNumInvestments OutDolProf OutPerProf
OutNetGains OutLong OutShort OutInvestment OutStoploss OutComission
OutPenny OutVolume OutNumU OutAccDefn
investment 30000 3 -450
-0.015 -0.0154 0.75 -0.5 10000 -0.015
2e-04 3 0.02 2 0
[[2]]
OutTotInvestment OutNumInvestments OutDolProf OutPerProf
OutNetGains OutLong OutShort OutInvestment OutStoploss OutComission
OutPenny OutVolume OutNumU OutAccDefn
investment 30000 3 -450
-0.015 -0.0154 1.5 -0.5 10000 -0.015
2e-04 3 0.02 2 0
...
When I try to apply 'as.data.frame', it concatenates incremental
numbers to the repeated row headers and gives:
as.data.frame(Results2)
OutTotInvestment OutNumInvestments OutDolProf OutPerProf
OutNetGains OutLong OutShort OutInvestment OutStoploss OutComission
OutPenny OutVolume OutNumU OutAccDefn
investment 30000 3 -450
-0.015 -0.0154 0.75 -0.5 10000 -0.015
2e-04 3 0.02 2 0
OutTotInvestment.1 OutNumInvestments.1 OutDolProf.1
OutPerProf.1 OutNetGains.1 OutLong.1 OutShort.1 OutInvestment.1
OutStoploss.1 OutComission.1 OutPenny.1
investment 30000 3 -450
-0.015 -0.0154 1.5 -0.5 10000
-0.015 2e-04 3
OutVolume.1 OutNumU.1 OutAccDefn.1 OutTotInvestment.2
OutNumInvestments.2 OutDolProf.2 OutPerProf.2 OutNetGains.2 OutLong.
2 OutShort.2 OutInvestment.2
investment 0.02 2 0
30000 3 -450 -0.015
-0.0154 0.75 -1 10000
...
which is a data frame of dimension 1 224, when I am looking for a
data frame like Results of dimension 16 14.
------------------------------------------------------------------------------------------------------------------------------
Reproducible code:
------------------------------------------------------------------------------------------------------------------------------
# --------------------------------------------------------------
# FUNCTION calcProfit
# --------------------------------------------------------------
calcProfit <- function(IterParam, marketData, dailyForecast) #,
long, short, investment, stoploss, comission, penny, volume, numU,
accDefn)
{
if (class(IterParam) == "numeric")
{
long <- IterParam["long"]
short <- IterParam["short"]
investment <- IterParam["investment"]
stoploss <- IterParam["stoploss"]
comission <- IterParam["comission"]
penny <- IterParam["penny"]
volume <- IterParam["volume"]
numU <- IterParam["numU"]
accDefn <- IterParam["accDefn"]
} else {
long <- IterParam$long
short <- IterParam$short
investment <- IterParam$investment
stoploss <- IterParam$stoploss
comission <- IterParam$comission
penny <- IterParam$penny
volume <- IterParam$volume
numU <- IterParam$numU
accDefn <- IterParam$accDefn
}
compareMarket <- merge(dailyForecast, marketData,
by.x="SymbolID", by.y="SymbolID")
weight <- ifelse(rep(accDefn, times=length(compareMarket
$weight))==1, compareMarket$weight, compareMarket$CPweight)
position <- ifelse((weight<=short & compareMarket$OpeningPrice >
penny & compareMarket$noU>=numU), "S",
ifelse((weight>=long & compareMarket$OpeningPrice > penny &
compareMarket$noU>=numU), "L", NA))
positionTF <- ifelse(position=="L" | position=="S", TRUE, FALSE)
estMaxInv <- volume*compareMarket$MinTrVol*compareMarket
$YesterdayClose
investbySymbol <- ifelse(positionTF==TRUE, ifelse(estMaxInv >=
investment, investment, 0))
opClProfit <- ifelse(position=="L", compareMarket$ClosingPrice/
compareMarket$OpeningPrice-1,
ifelse(position=="S", 1-compareMarket
$ClosingPrice/compareMarket$OpeningPrice, 0.0))
Gains <- investbySymbol*ifelse(opClProfit <= stoploss, stoploss,
opClProfit)
ProfitTable <- data.frame(SymbolID=compareMarket$SymbolID,
investbySymbol, Gains, percentGains=Gains/investbySymbol,
LessComm=rep(comission,
times=length(Gains)), NetGains=Gains/investbySymbol-2*comission)
AggregatesTable <- data.frame( OutTotInvestment = sum(ProfitTable
$investbySymbol, na.rm=TRUE),
OutNumInvestments = sum(ProfitTable$investbySymbol,
na.rm=TRUE)/investment, OutDolProf = sum(ProfitTable$Gains,
na.rm=TRUE),
OutPerProf = sum(ProfitTable$Gains, na.rm=TRUE)/
sum(ProfitTable$investbySymbol, na.rm=TRUE),
OutNetGains = sum(ProfitTable$Gains, na.rm=TRUE)/
sum(ProfitTable$investbySymbol, na.rm=TRUE)-2*comission, OutLong =
long,
OutShort = short, OutInvestment = investment, OutStoploss =
stoploss, OutComission = comission, OutPenny = penny, OutVolume =
volume,
OutNumU = numU, OutAccDefn = accDefn )
return(AggregatesTable)
}
# Sample iteration parameters (these can be vectors of arbitrary
length)
# Need to iterate through all possible combinations of these
parameters
Param <- list(long=c(.75, 1.5),
short=c(-.5, -1),
investment=10000,
stoploss=c(-.015),
comission=.0002,
penny=3,
volume=c(.02, .01),
numU=2,
accDefn=0:1 )
CombParam <- expand.grid(Param)
# Create sample X and Y data frames for function call
Y <- data.frame(SymbolID=10:14, OpeningPrice = c(1,3,10,20,60),
ClosingPrice = c(2,2.5,11,18,61.5), YesterdayClose= c(1,3,10,20,60),
MinTrVol = rep(10000000, times=5))
X <- data.frame(SymbolID=10:14, weight = c(1, .5, -3, -.75, 2),
CPweight=c(1.5, .25, -1.75, 2, -1), noU = c(2,3,4,2,10))
for (i in 1:length(CombParam$long))
{
if(i==1)
{ Results <- calcProfit(CombParam[i,], X, Y)
} else {
Results <- rbind(Results, calcProfit(CombParam[i,], X, Y))
}
}
Results2 <- apply(CombParam, 1, calcProfit, X, Y)
------------------------------------------------------------------------------------------------------------------------------
On Tue, Dec 23, 2008 at 11:15 AM, David Winsemius <dwinsem...@comcast.net
> wrote:
On Dec 23, 2008, at 10:56 AM, Brigid Mooney wrote:
Thank you again for your help.
snip
-------------
With the 'apply' call, Results2 is of class list.
Results2 <- apply(CombParam, 1, calcProfit, X, Y)
-------------------------------------------------------------------------------------------------------
How can I get convert Results2 from a list to a data frame like
Results?
Have you tried as.data.frame() on Results2? Each of its elements
should have the proper structure.
You no longer have a reproducible example, but see this session clip:
> lairq <- apply(airquality,1, function(x) x )
> str(lairq)
num [1:6, 1:153] 41 190 7.4 67 5 1 36 118 8 72 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:6] "Ozone" "Solar.R" "Wind" "Temp" ...
..$ : NULL
> is.data.frame(lairq)
[1] FALSE
> is.data.frame(rbind(lairq))
[1] FALSE
> is.data.frame( as.data.frame(lairq) )
--
David Winsemius
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