cumulative sum by group and under some criteria
HI,
I think this should be more correct:
maxN<-9?
c11<-0.2?
c12<-0.2?
p0L<-0.05?
p0H<-0.05?
p1L<-0.20?
p1H<-0.20?
d <-?structure(list(m1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,?
2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3),?
? ? n1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3,?
? ? 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), x1 = c(0,?
? ? 0, 0, 1, 1, 1, 2, 2, 2, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2,?
? ? 2, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3), y1 = c(0, 1, 2, 0,?
? ? 1, 2, 0, 1, 2, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1,?
? ? 2, 0, 1, 2, 0, 1, 2, 0, 1, 2), Fmm = c(0, 0, 0, 0.7, 0.59,?
? ? 0.64, 1, 1, 1, 0, 0, 0, 0, 0.63, 0.7, 0.74, 0.68, 1, 1, 1,?
? ? 1, 0, 0, 0, 0.62, 0.63, 0.6, 0.63, 0.6, 0.68, 1, 1, 1), Fnn = c(0,?
? ? 0.64, 1, 0, 0.51, 1, 0, 0.67, 1, 0, 0.62, 0.69, 1, 0, 0.54,?
? ? 0.62, 1, 0, 0.63, 0.73, 1, 0, 0.63, 1, 0, 0.7, 1, 0, 0.7,?
? ? 1, 0, 0.58, 1), Qm = c(1, 1, 1, 0.65, 0.45, 0.36, 0.5, 0.165,?
? ? 0, 1, 1, 1, 1, 0.685, 0.38, 0.32, 0.32, 0.5, 0.185, 0.135,?
? ? 0, 1, 1, 1, 0.69, 0.37, 0.4, 0.685, 0.4, 0.32, 0.5, 0.21,?
? ? 0), Qn = c(1, 0.36, 0, 0.65, 0.45, 0, 0.5, 0.165, 0, 1, 0.38,?
? ? 0.31, 0, 0.685, 0.38, 0.32, 0, 0.5, 0.185, 0.135, 0, 1, 0.37,?
? ? 0, 0.69, 0.3, 0, 0.685, 0.3, 0, 0.5, 0.21, 0), term1_p0 = c(0.81450625,?
? ? 0.0857375, 0.00225625, 0.0857375, 0.009025, 0.0002375, 0.00225625,?
? ? 0.0002375, 6.25e-06, 0.7737809375, 0.1221759375, 0.00643031249999999,?
? ? 0.0001128125, 0.081450625, 0.012860625, 0.000676875, 1.1875e-05,?
? ? 0.0021434375, 0.0003384375, 1.78125e-05, 3.125e-07, 0.7737809375,?
? ? 0.081450625, 0.0021434375, 0.1221759375, 0.012860625, 0.0003384375,?
? ? 0.00643031249999999, 0.000676875, 1.78125e-05, 0.0001128125,?
? ? 1.1875e-05, 3.125e-07), term1_p1 = c(0.4096, 0.2048, 0.0256,?
? ? 0.2048, 0.1024, 0.0128, 0.0256, 0.0128, 0.0016, 0.32768,?
? ? 0.24576, 0.06144, 0.00512, 0.16384, 0.12288, 0.03072, 0.00256,?
? ? 0.02048, 0.01536, 0.00384, 0.00032, 0.32768, 0.16384, 0.02048,?
? ? 0.24576, 0.12288, 0.01536, 0.06144, 0.03072, 0.00384, 0.00512,?
? ? 0.00256, 0.00032)), .Names = c("m1", "n1", "x1", "y1", "Fmm",?
"Fnn", "Qm", "Qn", "term1_p0", "term1_p1"), row.names = c(NA,?
33L), class = "data.frame")
library(zoo)
lst1<- split(d,list(d$m1,d$n1))
res2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
x[,11:14]<-NA;
x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]);
x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]);
colnames(x)[11:14]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H");
x1<-na.locf(x);
x1[,11:14][is.na(x1[,11:14])]<-0;
x1}))
row.names(res2)<- 1:nrow(res2)
?res2
?# ?m1 n1 x1 y1 ?Fmm ?Fnn ? ?Qm ? ?Qn ? ? term1_p0 term1_p1 ? cterm1_P0L cterm1_P1L ? cterm1_P0H cterm1_P1H
#1 ? 2 ?2 ?0 ?0 0.00 0.00 1.000 1.000 0.8145062500 ?0.40960 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#2 ? 2 ?2 ?0 ?1 0.00 0.64 1.000 0.360 0.0857375000 ?0.20480 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#3 ? 2 ?2 ?0 ?2 0.00 1.00 1.000 0.000 0.0022562500 ?0.02560 0.0000000000 ? ?0.00000 0.0022562500 ? ?0.02560
#4 ? 2 ?2 ?1 ?0 0.70 0.00 0.650 0.650 0.0857375000 ?0.20480 0.0000000000 ? ?0.00000 0.0022562500 ? ?0.02560
#5 ? 2 ?2 ?1 ?1 0.59 0.51 0.450 0.450 0.0090250000 ?0.10240 0.0000000000 ? ?0.00000 0.0022562500 ? ?0.02560
#6 ? 2 ?2 ?1 ?2 0.64 1.00 0.360 0.000 0.0002375000 ?0.01280 0.0000000000 ? ?0.00000 0.0024937500 ? ?0.03840
#7 ? 2 ?2 ?2 ?0 1.00 0.00 0.500 0.500 0.0022562500 ?0.02560 0.0000000000 ? ?0.00000 0.0024937500 ? ?0.03840
#8 ? 2 ?2 ?2 ?1 1.00 0.67 0.165 0.165 0.0002375000 ?0.01280 0.0002375000 ? ?0.01280 0.0027312500 ? ?0.05120
#9 ? 2 ?2 ?2 ?2 1.00 1.00 0.000 0.000 0.0000062500 ?0.00160 0.0002437500 ? ?0.01440 0.0027375000 ? ?0.05280
#10 ?3 ?2 ?0 ?0 0.00 0.00 1.000 1.000 0.7737809375 ?0.32768 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#11 ?3 ?2 ?0 ?1 0.00 0.63 1.000 0.370 0.0814506250 ?0.16384 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#12 ?3 ?2 ?0 ?2 0.00 1.00 1.000 0.000 0.0021434375 ?0.02048 0.0000000000 ? ?0.00000 0.0021434375 ? ?0.02048
#13 ?3 ?2 ?1 ?0 0.62 0.00 0.690 0.690 0.1221759375 ?0.24576 0.0000000000 ? ?0.00000 0.0021434375 ? ?0.02048
#14 ?3 ?2 ?1 ?1 0.63 0.70 0.370 0.300 0.0128606250 ?0.12288 0.0000000000 ? ?0.00000 0.0021434375 ? ?0.02048
#15 ?3 ?2 ?1 ?2 0.60 1.00 0.400 0.000 0.0003384375 ?0.01536 0.0000000000 ? ?0.00000 0.0024818750 ? ?0.03584
#16 ?3 ?2 ?2 ?0 0.63 0.00 0.685 0.685 0.0064303125 ?0.06144 0.0000000000 ? ?0.00000 0.0024818750 ? ?0.03584
#17 ?3 ?2 ?2 ?1 0.60 0.70 0.400 0.300 0.0006768750 ?0.03072 0.0000000000 ? ?0.00000 0.0024818750 ? ?0.03584
#18 ?3 ?2 ?2 ?2 0.68 1.00 0.320 0.000 0.0000178125 ?0.00384 0.0000000000 ? ?0.00000 0.0024996875 ? ?0.03968
#19 ?3 ?2 ?3 ?0 1.00 0.00 0.500 0.500 0.0001128125 ?0.00512 0.0000000000 ? ?0.00000 0.0024996875 ? ?0.03968
#20 ?3 ?2 ?3 ?1 1.00 0.58 0.210 0.210 0.0000118750 ?0.00256 0.0000000000 ? ?0.00000 0.0024996875 ? ?0.03968
#21 ?3 ?2 ?3 ?2 1.00 1.00 0.000 0.000 0.0000003125 ?0.00032 0.0000003125 ? ?0.00032 0.0025000000 ? ?0.04000
#22 ?2 ?3 ?0 ?0 0.00 0.00 1.000 1.000 0.7737809375 ?0.32768 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#23 ?2 ?3 ?0 ?1 0.00 0.62 1.000 0.380 0.1221759375 ?0.24576 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#24 ?2 ?3 ?0 ?2 0.00 0.69 1.000 0.310 0.0064303125 ?0.06144 0.0000000000 ? ?0.00000 0.0000000000 ? ?0.00000
#25 ?2 ?3 ?0 ?3 0.00 1.00 1.000 0.000 0.0001128125 ?0.00512 0.0000000000 ? ?0.00000 0.0001128125 ? ?0.00512
#26 ?2 ?3 ?1 ?0 0.63 0.00 0.685 0.685 0.0814506250 ?0.16384 0.0000000000 ? ?0.00000 0.0001128125 ? ?0.00512
#27 ?2 ?3 ?1 ?1 0.70 0.54 0.380 0.380 0.0128606250 ?0.12288 0.0000000000 ? ?0.00000 0.0001128125 ? ?0.00512
#28 ?2 ?3 ?1 ?2 0.74 0.62 0.320 0.320 0.0006768750 ?0.03072 0.0000000000 ? ?0.00000 0.0001128125 ? ?0.00512
#29 ?2 ?3 ?1 ?3 0.68 1.00 0.320 0.000 0.0000118750 ?0.00256 0.0000000000 ? ?0.00000 0.0001246875 ? ?0.00768
#30 ?2 ?3 ?2 ?0 1.00 0.00 0.500 0.500 0.0021434375 ?0.02048 0.0000000000 ? ?0.00000 0.0001246875 ? ?0.00768
#31 ?2 ?3 ?2 ?1 1.00 0.63 0.185 0.185 0.0003384375 ?0.01536 0.0003384375 ? ?0.01536 0.0004631250 ? ?0.02304
#32 ?2 ?3 ?2 ?2 1.00 0.73 0.135 0.135 0.0000178125 ?0.00384 0.0003562500 ? ?0.01920 0.0004809375 ? ?0.02688 ?
#33 ?2 ?3 ?2 ?3 1.00 1.00 0.000 0.000 0.0000003125 ?0.00032 0.0003565625 ? ?0.01952 0.0004812500 ? ?0.02720
#Sorry, some values in my previous solution didn't look right. I didn't?
A.K.
----- Original Message -----
From: Zjoanna <Zjoanna2013 at gmail.com>
To: r-help at r-project.org
Cc:
Sent: Friday, February 1, 2013 12:19 PM
Subject: Re: [R] cumulative sum by group and under some criteria
Thank you very much for your reply. Your code work well with this example.
I modified a little to fit my real data, I got an error massage.
Error in split.default(x = seq_len(nrow(x)), f = f, drop = drop, ...) :
? Group length is 0 but data length > 0
On Thu, Jan 31, 2013 at 12:21 PM, arun kirshna [via R] <
ml-node+s789695n4657196h87 at n4.nabble.com> wrote:
Hi,
Try this:
colnames(d)<-c("m1","n1","x1","y1","p11","p12")
library(zoo)
res1<- do.call(rbind,lapply(lapply(split(d,list(d$m1,d$n1)),function(x)
{x$cp11[x$x1>1]<- cumsum(x$p11[x$x1>1]);x$cp12[x$y1>1]<-
cumsum(x$p12[x$y1>1]);x}),function(x)
{x$cp11<-na.locf(x$cp11,na.rm=F);x$cp12<- na.locf(x$cp12,na.rm=F);x}))
#there would be a warning here as one of the list element is NULL.? The,
warning is okay
row.names(res1)<- 1:nrow(res1)
res1[,7:8][is.na(res1[,7:8])]<- 0
res1
? #? m1 n1 x1 y1? p11? p12 cp11 cp12
#1? 2? 2? 0? 0 0.00 0.00 0.00 0.00
#2? 2? 2? 0? 1 0.00 0.50 0.00 0.00
#3? 2? 2? 0? 2 0.00 1.00 0.00 1.00
#4? 2? 2? 1? 0 0.50 0.00 0.00 1.00
#5? 2? 2? 1? 1 0.50 0.50 0.00 1.00
#6? 2? 2? 1? 2 0.50 1.00 0.00 2.00
#7? 2? 2? 2? 0 1.00 0.00 1.00 2.00
#8? 2? 2? 2? 1 1.00 0.50 2.00 2.00
#9? 2? 2? 2? 2 1.00 1.00 3.00 3.00
#10? 3? 2? 0? 0 0.00 0.00 0.00 0.00
#11? 3? 2? 0? 1 0.00 0.50 0.00 0.00
#12? 3? 2? 0? 2 0.00 1.00 0.00 1.00
#13? 3? 2? 1? 0 0.33 0.00 0.00 1.00
#14? 3? 2? 1? 1 0.33 0.50 0.00 1.00
#15? 3? 2? 1? 2 0.33 1.00 0.00 2.00
#16? 3? 2? 2? 0 0.67 0.00 0.67 2.00
#17? 3? 2? 2? 1 0.67 0.50 1.34 2.00
#18? 3? 2? 2? 2 0.67 1.00 2.01 3.00
#19? 3? 2? 3? 0 1.00 0.00 3.01 3.00
#20? 3? 2? 3? 1 1.00 0.50 4.01 3.00
#21? 3? 2? 3? 2 1.00 1.00 5.01 4.00
#22? 2? 3? 0? 0 0.00 0.00 0.00 0.00
#23? 2? 3? 0? 1 0.00 0.33 0.00 0.00
#24? 2? 3? 0? 2 0.00 0.67 0.00 0.67
#25? 2? 3? 0? 3 0.00 1.00 0.00 1.67
#26? 2? 3? 1? 0 0.50 0.00 0.00 1.67
#27? 2? 3? 1? 1 0.50 0.33 0.00 1.67
#28? 2? 3? 1? 2 0.50 0.67 0.00 2.34
#29? 2? 3? 1? 3 0.50 1.00 0.00 3.34
#30? 2? 3? 2? 0 1.00 0.00 1.00 3.34
#31? 2? 3? 2? 1 1.00 0.33 2.00 3.34
#32? 2? 3? 2? 2 1.00 0.67 3.00 4.01
#33? 2? 3? 2? 3 1.00 1.00 4.00 5.01
A.K.
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