[R] Result error using the function
smart hendsome
putra_autumn86 at yahoo.com
Tue Oct 6 08:33:42 CEST 2015
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,
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1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L, 1950L,
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1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
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1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
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1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
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1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L, 1951L,
1951L, 1951L, 1951L, 1951L), Month = c(1L, 1L, 1L, 1L, 1L, 1L,
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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,
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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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