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grow <- function(x){diff(x)/x[-length(x)]} #a rate of change. | |
cont <- function(a,all){ #contribution | |
grow(a) * (a/all)[-length(a)] | |
} |
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dat_somusho <- | |
structure(list(sex = structure(c(2L, 1L), .Label = c("female", | |
"male"), class = "factor"), `6-12` = c(1679437.5, 1743009.6), | |
`13-19` = c(2366812.5, 2450792.4), `20-29` = c(2352187.5, | |
2468424), `30-39` = c(2308312.5, 2415529.2), `40-49` = c(2327812.5, | |
2375228.4), `50-59` = c(2169375, 2057859.6), `60-64` = c(1925625, | |
1624626), `65-69` = c(1713562.5, 1377783.6), `70-79` = c(1464937.5, | |
974775.6), `80+` = c(975000, 445827.6)), .Names = c("sex", | |
"6-12", "13-19", "20-29", "30-39", "40-49", "50-59", "60-64", | |
"65-69", "70-79", "80+"), row.names = c("男性(n=24,375)", "女性(n=25,188)" |
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as.Date4ga <- function(x){ | |
nc <-nchar(x) | |
y <- substr(x,1,4) | |
m <-substr(x,5,6) | |
d <-substr(x,7,8) | |
t1 <-ifelse(nc==6,paste(y,m,"01",sep="/"),paste(y,m,d,sep="/")) | |
as.Date(t1) | |
} |
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crossbreed <- function(KW){ | |
dim1 <-dim(KW) | |
lis1 <- list() | |
for(i in 1:dim1[2]){ | |
lis1[[i]] <- KW[!is.na(KW[,i]),i] | |
} | |
lenv <- sapply(lis1,length) | |
#lenv | |
#lis1 | |
# out <- numeric(prod(lenv)) |
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日の指標 | セッション | |
---|---|---|
2014/11/25 | 256 | |
2014/11/26 | 174 | |
2014/11/27 | 188 | |
2014/11/28 | 157 | |
2014/11/29 | 91 | |
2014/11/30 | 96 | |
2014/12/01 | 170 | |
2014/12/02 | 183 | |
2014/12/03 | 135 |
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punc <- function(x){ | |
len = length(x) | |
pp <- which(x > 1.5*IQR(x) + quantile(x,3/4)) | |
pplen <- length(pp) | |
group <- rep(1,len) | |
group[pp] <- 1 | |
if(pplen==0){ | |
return(group) | |
break | |
} |
We can make this file beautiful and searchable if this error is corrected: It looks like row 6 should actually have 1 column, instead of 3 in line 5.
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# ---------------------------------------- | |
# すべてのウェブサイトのデータ | |
# コンバージョン経路 | |
# 20141101-20150131 | |
# ---------------------------------------- | |
MCF チャネル グループの経路,コンバージョン数,コンバージョン値 | |
オーガニック検索 > ノーリファラー,22,$0.00 | |
ソーシャル ネットワーク > ノーリファラー,16,$0.00 | |
ソーシャル ネットワーク > ソーシャル ネットワーク,14,$0.00 |
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"","channelGrouping","sessions","percentNewSessions","bounceRate","avgSessionDuration","pageviewsPerSession" | |
"1","(Other)",249,39.3574297188755,77.5100401606426,117.979919678715,1.61044176706827 | |
"2","Direct",1743,90.5909351692484,84.6242111302352,78.5100401606426,1.35226620768789 | |
"3","Organic Search",5703,84.5344555497107,84.7273364895669,58.9933368402595,1.28949675609328 | |
"4","Referral",2792,83.8467048710602,89.756446991404,44.6719197707736,1.24104584527221 | |
"5","Social",5193,79.3568264972078,85.7500481417293,56.7113421914115,1.32851916040824 |
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library(ReacTran) | |
library(deSolve) | |
N <- 100 | |
xgrid <- setup.grid.1D(x.up = 0, x.down = 1, N = N) | |
x <- xgrid$x.mid | |
D.coeff <- 0.01 | |
Diffusion <- function (t, Y, parms){ | |
tran <- tran.1D(C = Y, C.up = 0, C.down = 1, | |
D = D.coeff, dx = xgrid) | |
list(dY = tran$dC, flux.up = tran$flux.up, |
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waterfall <-function(left,right,group,leftname ="",rightname ="", | |
xlab="",ylab="",leftcol="grey80",rightcol="grey80",cols=NULL){ | |
sum1 =sum(left) | |
sum2 =sum(right) | |
tmp1 <- c(cumsum(c(sum1,right-left)),sum2) | |
len <-length(left) | |
bp <- barplot(c(sum1,rep(0,len),sum2), | |
space=0,yaxt="n",xaxt="n", | |
col=c(leftcol,rep("white",len),rightcol), | |
xlab=xlab,ylab=ylab) |