target <- 100000
breakpts <- data.frame( PctTarget=c(50,75,100,Inf), Mult=c(2,4,8,10) )
breakpts$LastPct <- c( 0, breakpts$PctTarget[ -nrow( breakpts ) ] )
breakpts$Range <- cut( breakpts$PctTarget, c( 0, breakpts$PctTarget ),
include.lowest=TRUE )
breakpts$DeltaPct <- with( breakpts, diff( c( 0, PctTarget ) ) )
breakpts$CumMARGE <- target / 1e4 * with( breakpts, cumsum( DeltaPct *
Mult ) )
breakpts$LastCumMARGE <- c( 0, breakpts$CumMARGE[ -nrow( breakpts ) ] )
dta <- data.frame( ID=11:14, VALUE=c(10000,50000,30000,20000) )
dta$CumVALUE <- cumsum( dta$VALUE )
dta$CumPct <- 100 * dta$CumVALUE / target
dta$Range <- cut( dta$CumPct, c( 0, breakpts$PctTarget ),
include.lowest=TRUE )
dta
ID VALUE CumVALUE CumPct Range
1 11 10000 10000 10 [0,50]
2 12 50000 60000 60 (50,75]
3 13 30000 90000 90 (75,100]
4 14 20000 110000 110 (100,Inf]
breakpts
PctTarget Mult LastPct Range DeltaPct CumMARGE LastCumMARGE
1 50 2 0 [0,50] 50 1000 0
2 75 4 50 (50,75] 25 2000 1000
3 100 8 75 (75,100] 25 4000 2000
4 Inf 10 100 (100,Inf] Inf Inf 4000
#dta2 <- merge( dta, breakpts, all.x=TRUE, by="Range" )
#dta2 <- dta2[ order( dta2$ID ), ]
dta2 <- cbind( dta, breakpts[ match( dta$Range, breakpts$Range ),
-which( "Range"==names( breakpts ) ) ] )
dta2$CumMARGE <- with( dta2, Mult/100 * ( CumVALUE - target * LastPct /
100 ) + LastCumMARGE )
dta2$MARGE <- with( dta2, diff( c( 0, CumMARGE ) ) )
dta2
ID VALUE CumVALUE CumPct Range PctTarget Mult LastPct DeltaPct
CumMARGE LastCumMARGE MARGE
1 11 10000 10000 10 [0,50] 50 2 0 50
200 0 200
2 12 50000 60000 60 (50,75] 75 4 50 25
1400 1000 1200
3 13 30000 90000 90 (75,100] 100 8 75 25
3200 2000 1800
4 14 20000 110000 110 (100,Inf] Inf 10 100 Inf
5000 4000 1800
target <- 100000
breakpts <- data.frame( PctTarget=c(50,75,100,Inf), Mult=c(2,4,8,10) )
breakpts$LastPct <- c( 0, breakpts$PctTarget[ -nrow( breakpts ) ] )
breakpts$Range <- cut( breakpts$PctTarget, c( 0, breakpts$PctTarget ),
include.lowest=TRUE )
breakpts$DeltaPct <- with( breakpts, diff( c( 0, PctTarget ) ) )
breakpts$CumMARGE <- target / 1e4 * with( breakpts, cumsum( DeltaPct *
Mult ) )
breakpts$LastCumMARGE <- c( 0, breakpts$CumMARGE[ -nrow( breakpts ) ] )
dta <- data.frame( ID=11:14, VALUE=c(10000,50000,30000,20000) )
dta$CumVALUE <- cumsum( dta$VALUE )
dta$CumPct <- 100 * dta$CumVALUE / target
dta$Range <- cut( dta$CumPct, c( 0, breakpts$PctTarget ),
include.lowest=TRUE )
dta
ID VALUE CumVALUE CumPct Range
1 11 10000 10000 10 [0,50]
2 12 50000 60000 60 (50,75]
3 13 30000 90000 90 (75,100]
4 14 20000 110000 110 (100,Inf]
breakpts
PctTarget Mult LastPct Range DeltaPct CumMARGE LastCumMARGE
1 50 2 0 [0,50] 50 1000 0
2 75 4 50 (50,75] 25 2000 1000
3 100 8 75 (75,100] 25 4000 2000
4 Inf 10 100 (100,Inf] Inf Inf 4000
#dta2 <- merge( dta, breakpts, all.x=TRUE, by="Range" )
#dta2 <- dta2[ order( dta2$ID ), ]
dta2 <- cbind( dta, breakpts[ match( dta$Range, breakpts$Range ),
-which( "Range"==names( breakpts ) ) ] )
dta2$CumMARGE <- with( dta2, Mult/100 * ( CumVALUE - target * LastPct /
100 ) + LastCumMARGE )
dta2$MARGE <- diff( c( 0, dta2$CumMARGE ) )
dta2
ID VALUE CumVALUE CumPct Range PctTarget Mult LastPct DeltaPct
CumMARGE LastCumMARGE MARGE
1 11 10000 10000 10 [0,50] 50 2 0 50
200 0 200
2 12 50000 60000 60 (50,75] 75 4 50 25
1400 1000 1200
3 13 30000 90000 90 (75,100] 100 8 75 25
3200 2000 1800
4 14 20000 110000 110 (100,Inf] Inf 10 100 Inf
5000 4000 1800
On Mon, 9 Mar 2015, Matthias Weber wrote:
Hi David,
thanks for the reply. My spelling of the numbers was not correct. What I mean
with 100.000 is 100000.00 !
I have corrected the values in my example below me.
Maybe you can understand it better now.
Crucially is, that the "MARGE" rises up in dependence of the ID. The ID 11 will
be count with 2% because we don't reach the 50% hurdle (50000). The ID 12 will reach the
50% hurdle, so the ID 12 should be count with 1200 (result of 40000 * 2% + 10000 * 4%).
The 10000 with 4% will be credited more, because they exceed the 50% Target Value.
Thanks for your help.
Best regards.
Mat
-----Urspr?ngliche Nachricht-----
Von: David L Carlson [mailto:dcarl...@tamu.edu]
Gesendet: Montag, 9. M?rz 2015 16:08
An: Matthias Weber; r-help@r-project.org
Betreff: RE: calculate value in dependence of target value
It is very hard to figure out what you are trying to do.
1. All of the VALUEs are greater than the target of 100 2. Your description of
what you want does not match your example.
Perhaps VALUE should be divided by 1000 (e.g. not 10000, but 10)?
Perhaps your targets do not apply to VALUE, but to cumulative VALUE?
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Matthias Weber
Sent: Monday, March 9, 2015 7:46 AM
To: r-help@r-project.org
Subject: [R] calculate value in dependence of target value
Hello together,
i have a litte problem. Maybe anyone can help me.
I have to calculate a new column in dependence of a target value.
As a example: My target value is 100000. At the moment I have a data.frame with
the following values.
ID VALUE
1 11 10000
2 12 50000
3 13 30000
4 14 20000
The new column ("MARGE") should be calculated with the following graduation:
Until the VALUE reach 50% of the target value (50000) = 2%
Until the VALUE reach 75% of the target value (75000) = 4%
Until the VALUE reach 100% of the target value (<100000) = 8%
If the VALUE goes above 100% of the value (>100000) = 10%
The result looks like this one:
ID VALUE MARGE
1 11 10000 200 (result of 10000 * 2%)
2 12 50000 1200 (result of 40000 * 2% + 10000 * 4%)
3 13 30000 1800 (result of 15000 * 4% + 15000 * 8%)
4 14 20000 1800 (result of 10000 * 8% + 10000 * 10%)
Is there anyway to calculate the column "MARGE" automatically in R?
Thanks a lot for your help.
Best regards.
Mat
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