I have a dataframe (df) like this.
df <- data.frame(prox)
year month day Tmean
`<dbl> <dbl> <dbl> <dbl>`
1 1956 1 1 13.5
2 1956 1 2 11.9
3 1956 1 3 9.71
4 1956 1 4 8.65
5 1956 1 5 4.51
6 1956 1 6 4.64
7 1956 1 7 6.66
8 1956 1 8 7.48
9 1956 1 9 5.56
10 1956 1 10 7.51
I want to find the maximum number of consecutive days with a decrease in temperature. So, I did this (with the help of @Andre Wildberg) for a single year and it works.
y <- rle(diff(df$Tmean) < 0)
max(y$lengths[y$values], na.rm=TRUE)
# [1] 6
But now, I want to find this, for each year (1956,1957,...). So, i' m trying to do this with group_by, but there is problem as rle is a list. Is it possible to do this somehow, or I have to find another way to do it?
df %>% group_by(year) %>%
summarise(x=list(rle(diff(df$Tmean) < 0)))
year x
<dbl> <list>
1 1956 <rle>
2 1957 <rle>
3 1958 <rle>
We can use with to subset the lengths based on the values and get the max of the lengths after grouping by 'year'
library(dplyr)
df %>%
group_by(year) %>%
summarise(x = with(rle(diff(Tmean) < 0),
max(lengths[values], na.rm = TRUE))
)
Or using base R
f1 <- function(x) {
y <- rle(diff(x) < 0)
max(y$lengths[y$values], na.rm = TRUE)}
aggregate(Tmean ~ year, df, f1)