Petr,
thank you very much, this pointed me in the right direction (to refine
my Google search :-)-O):
library(tidyverse)
library(coronavirus)
library(zoo)
as_tibble(coronavirus) %>%
filter(country=='Namibia' & type=="confirmed") %>%
mutate(rollsum = rollapplyr(cases, 7, sum, partial=TRUE)) %>%
arrange(desc(date)) %>%
mutate(R7=rollsum / 25.4 ) %>%
select(date,R7)
gives me something like
# A tibble: 573 × 2
date R7
<date> <dbl>
1 2021-08-16 52.8
2 2021-08-15 56.1
3 2021-08-14 55.6
4 2021-08-13 63.1
5 2021-08-12 62.8
6 2021-08-11 63.7
7 2021-08-10 67.3
8 2021-08-09 69.3
9 2021-08-08 69.2
10 2021-08-07 74.5
# … with 563 more rows
which seems to be correct :-)-O so I can now play with ggplot2 over the
weekend :-)-O
greetings, el
On 17/08/2021 12:46, PIKAL Petr wrote:
Hi.
There are several ways how to do it. You could find them easily using
Google. e.g.
https://stackoverflow.com/questions/19200841/consecutive-rolling-sums-in-a-vector-in-r
where you find several options.
Cheers
Petr
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