[R] Result error using the function
Adams, Jean
jvadams at usgs.gov
Wed Oct 7 03:17:20 CEST 2015
I have simplified your function. And I have transposed your results such
that resulting metrics are in columns rather than rows. So, it's not
exactly what you were after, but perhaps you will find it useful.
monthly_summary <- function(dt, r, tol=1E-6) {
# number of days with above tol by year and month
mt1 <- tapply(dt[, "Amount"] > tol, dt[, c("Month", "Year")], sum)
# mean number of days with above tol by month
mn <- apply(mt1, 1, mean)
# proportion of days with above tol by year and month
pd1 <- tapply(dt[, "Amount"] > tol, dt[, c("Month", "Year")], mean)
# mean proportion of days with above tol by month
mnp <- apply(mt1, 1, mean)
# inverse of this proportion
lambda <- 1/mnp
cbind(mt1, mn, lambda)
}
m_sum <- monthly_summary(J1, 2)
m_sum
Jean
On Tue, Oct 6, 2015 at 1:33 AM, smart hendsome <putra_autumn86 at yahoo.com>
wrote:
> Hi R-users,
>
>
> I am new to R. I try to code using the function in R as below:
> monthly_summary <- function(dt,r)
> { tol <- 1E-6
> mn <- vector(length=12, mode="numeric")
> lambda <- vector(length=12, mode="numeric")
> ag <- aggregate(dt[,4] > tol, list (dt[,2], dt[,1]), sum)
> names(ag) <- c("Year", "Month","Amount")
> mt1 <- matrix(ag[,3],nrow=r,ncol=12,byrow=T)
> rownames(mt1) <- 1950:1951
> colnames(mt1) <- c("Jan","Feb","Mar","Apr","May","June","July",
> "Aug","Sept","Oct","Nov","Dec")
>
> for (i in 1:ncol(mt1))
> {
> { xi <- mt1[,i]
> mn[i] <- mean(xi) ## calc mean
> }
>
> if (mt1[,c(1,3,5,7,8,10,12)])
> {
> lambda[i] <- (31/mn[i]) ## calc lambda
> for month with 31 days
> }
> else if (mt1[,2])
> {
> lambda[i] <- (28/mn[i]) ## calc lambda
> for month with 28 days
> }
> else
> {
> lambda[i] <- (30/mn[i]) ## calc lambda
> for month with 30 days
> }
>
> ## result
> mt1 <- round(mt1, 0)
> mn <- round(mn, 3)
> lambda <- round(lambda, 3)
>
> }
> comb <- rbind(mt1, mn = mn, lambda = lambda)
> }
>
> ## call function
> m_sum <- monthly_summary(J1,2); m_sum
>
> The problems are:
> 1)the value of count rain in decimals
> 2) the value lambda is wrong3)i dont know how to account the leap years in
> february
> Anyone can help me?
> I also provide my data using dput(). Thanks so much.
> structure(list(Year = c(1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
> 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
> 1951L, 1951L, 1951L, 1951L), Month = c(1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
> 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
> 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
> 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L,
> 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
> 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L,
> 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
> 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L,
> 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
> 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L,
> 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
> 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
> 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
> 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
> 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
> 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
> 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
> 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
> 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
> 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
> 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
> 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
> 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
> 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
> 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
> 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L,
> 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
> 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
> 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
> 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
> 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L,
> 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
> 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L
> ), Day = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L,
> 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
> 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
> 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
> 22L, 23L, 24L, 25L, 26L, 27L, 28L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
> 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
> 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L,
> 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
> 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
> 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
> 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
> 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
> 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
> 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L,
> 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
> 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L,
> 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
> 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
> 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
> 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
> 25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
> 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
> 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L,
> 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
> 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L,
> 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
> 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
> 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
> 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
> 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L,
> 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
> 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 1L, 2L, 3L, 4L,
> 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
> 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
> 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
> 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
> 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
> 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
> 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
> 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
> 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L,
> 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
> 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L,
> 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
> 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
> 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
> 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
> 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L,
> 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
> 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L,
> 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
> 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
> 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L,
> 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
> 26L, 27L, 28L, 29L, 30L, 31L), Amount = c(0, 35.5, 17.8, 24.5,
> 12.3, 11.5, 5.7, 13.2, 11.3, 14.7, 11.9, 17.5, 8.1, 0.4, 0, 19.5,
> 10.7, 0.5, 12.7, 6.3, 16.1, 11.4, 1.7, 0.8, 0.4, 0, 2.9, 5.3,
> 2.9, 0.5, 5.9, 2.9, 0, 16.2, 15.5, 21.8, 11.4, 1.2, 0, 0, 0,
> 0, 1.3, 9.5, 4.4, 4.2, 2.1, 0, 0, 0, 0, 0, 0, 0, 28.4, 14.2,
> 0, 0, 3.3, 1.7, 4.9, 3.6, 12, 16.7, 5.5, 1.1, 0.6, 2.7, 1.3,
> 0, 0, 34.2, 43.8, 27.2, 10.6, 3.8, 2.3, 34, 16.7, 0, 47.1, 23.5,
> 28.9, 18.1, 4.8, 5.5, 3.3, 3, 1.2, 3.3, 1.7, 1.8, 1.7, 0.7, 17,
> 8.4, 7.7, 3.9, 5.9, 2.9, 0, 1, 0.5, 0.8, 0.4, 4.2, 2.1, 0, 0,
> 0, 17.9, 9, 1.7, 1.6, 5.1, 2.8, 0.6, 0.2, 1.7, 0.8, 2.5, 1.3,
> 3.2, 1.9, 0.3, 3.4, 1.7, 4.5, 2.3, 0, 1.7, 0.8, 0, 0, 0, 0, 0,
> 16.9, 13.8, 11.1, 5.5, 2.3, 0.8, 0, 0, 28.7, 26.2, 9.6, 1.8,
> 0, 0, 0, 0, 0, 0, 0.3, 0.2, 0, 0, 53.1, 26.6, 41.1, 20.6, 18.1,
> 9, 0, 0, 0, 0, 6.9, 3.5, 0, 13.5, 6.8, 0, 0, 17.7, 8.9, 0, 0.1,
> 0.1, 0, 11, 5.5, 1, 1.3, 6.5, 3.5, 0.2, 1.1, 0.6, 18.6, 28.8,
> 9.7, 4.4, 8.4, 3.1, 0, 0.5, 0.2, 15.7, 8.2, 0.2, 0, 0, 0, 0,
> 0, 0.8, 0.4, 5.1, 2.5, 0, 0, 3.3, 1.7, 3, 1.5, 0, 0, 0, 0, 0,
> 0, 9.8, 38.7, 17.6, 17.2, 39.2, 16.4, 0.5, 0, 0, 0, 0, 16.4,
> 11.4, 1.9, 18.8, 48.6, 19.6, 24.3, 19.4, 4.4, 20.5, 14.1, 2,
> 0, 0, 0, 0, 0, 0.1, 0.1, 22.5, 11.2, 0.8, 0.4, 0, 5.5, 2.8, 2.9,
> 1.4, 22.7, 16.1, 32.2, 25.2, 5.5, 0.2, 0, 0, 0, 35.7, 17.8, 1.5,
> 1.1, 0.2, 0, 3.3, 1.8, 6.5, 14.2, 10.2, 11.6, 4.6, 20.8, 10.7,
> 1.8, 2.5, 12, 32.6, 13.5, 1, 0.5, 12.7, 6.3, 0.3, 0.2, 5.7, 2.9,
> 0, 0, 29.6, 14.9, 7.7, 3.8, 11, 11.2, 2.9, 2.5, 1.3, 0.8, 25.7,
> 21.9, 13, 15.5, 5.7, 22, 11, 16.4, 32.7, 12.3, 0, 0, 6.9, 8.5,
> 3.3, 9.9, 5.9, 7.8, 14.3, 12.6, 3.6, 0.8, 0.7, 0.2, 0.3, 5.2,
> 2.5, 0, 0.8, 1.4, 0.5, 0, 2.7, 5.5, 15.1, 6.8, 0.5, 0.2, 6.4,
> 9.1, 6.5, 9.4, 3.8, 0, 0, 2.7, 1.3, 0, 7.6, 10.5, 3.4, 0, 6.2,
> 36.9, 16.9, 4.5, 20.2, 9.3, 0.2, 14, 46.1, 38.1, 9.3, 0.8, 51.1,
> 113, 52.2, 18.5, 29.2, 48.9, 41.7, 18.1, 10.4, 3.5, 7.6, 3.8,
> 0, 1.3, 31.1, 18.2, 1.5, 0, 0, 0, 0, 10.1, 5.1, 0, 0, 0, 0, 6.7,
> 3.4, 26.2, 13.8, 8.1, 3.9, 74.8, 48.7, 23.7, 15.4, 4.3, 8.3,
> 3.9, 19.1, 13.2, 2.8, 2.3, 6.1, 14.1, 5.7, 0, 0, 0, 0, 7.6, 39.7,
> 17.9, 0, 5.1, 4.5, 1.3, 0.2, 0, 0, 0, 0, 0, 0, 0, 32.5, 16.2,
> 0, 0.5, 0.2, 0, 2.3, 2.2, 0.5, 0, 9.3, 11.9, 4.8, 0.6, 0, 32.5,
> 18.8, 11.4, 5.1, 0, 17.1, 8.5, 1.1, 0.6, 4.7, 2.4, 36.4, 21.1,
> 1.4, 0, 0, 0, 0, 0, 0, 1.1, 0.6, 0, 3.2, 2.6, 3.2, 9.1, 19.9,
> 8, 0, 0, 7.1, 3.5, 6.2, 3.1, 0, 1.7, 13.5, 21.5, 7.6, 0, 0, 0,
> 0, 15.2, 7.6, 0, 0, 0, 5.4, 17.9, 7.6, 11.1, 6, 1.9, 6.7, 2.9,
> 29.1, 14.5, 14.3, 16.4, 4.6, 0, 0, 0, 0, 31.3, 15.6, 0, 0, 0,
> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14.3, 7.2, 0.8, 1.2, 30, 14.8,
> 0, 0, 0, 0, 0, 0, 0, 4.2, 2.1, 4.2, 3.8, 5, 44.4, 25.3, 2.9,
> 0.4, 0, 8.4, 4.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 31.1,
> 15.6, 0, 13.5, 6.8, 0, 0, 0.8, 0.4, 24.5, 12.6, 29.6, 14.7, 39.3,
> 19.6, 0, 0, 0, 0, 0, 0, 0, 5.7, 27.1, 12.1, 25.7, 18.9, 15.4,
> 6.2, 0, 3.2, 1.6, 0, 0, 0, 0, 0, 2.3, 1.2, 15.2, 13.3, 31.8,
> 17.5, 1.5, 1.3, 3.2, 1.3, 0, 0, 0, 0, 18.6, 9.3, 0, 0, 0, 3.3,
> 11.1, 36.9, 48.9, 24, 3.8, 0.8, 0.4, 0, 0, 0, 0, 0, 0, 0, 0,
> 4.2, 2.1, 0, 1.1, 0.6, 0.8, 0.4, 36.4, 18.2, 8.4, 22.3, 9, 0,
> 33.8, 17.7, 13.3, 6.4, 0.7, 0.3, 0, 0, 0, 10.3, 15.3, 12.3, 7.8,
> 2.1, 0, 0, 31.3, 15.6, 6.7, 19.4, 9.4, 0.7, 10.1, 5.9, 0.4, 0.8,
> 7.1, 3.4, 9.9, 5, 0, 6.6, 9.2, 2.9, 0.3, 0.2, 0.3, 17, 8.4, 7.1,
> 3.5, 15.2, 55.3, 75.1, 59.6, 17, 0, 0.5, 0.2, 2.9, 2.9, 3.7,
> 1.5, 0, 0, 0, 0, 2.5, 1.7, 0.2, 39.7, 19.9, 33, 16.5, 1.5, 0.7,
> 1.5, 0.9, 19.3)), .Names = c("Year", "Month", "Day", "Amount"
> ), class = "data.frame", row.names = c(NA, -730L))
>
>
>
>
>
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