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Dr Eberhard Lisse

2021-Aug-17 12:30 UTC

[R] Rolling 7 day incidence

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[...]


-- 
To email me replace 'nospam' with 'el'

PIKAL Petr

2021-Aug-17 13:09 UTC

head link

[R] Rolling 7 day incidence

Hi

You're wellcome. You probably know 

https://www.repidemicsconsortium.org/projects/

as a collection of tools for epidemy evaluation.

Cheers
Petr
> -----Original Message-----
> From: R-help <r-help-bounces at r-project.org> On Behalf Of Dr
Eberhard
> Lisse
> Sent: Tuesday, August 17, 2021 2:30 PM
> To: r-help at r-project.org
> Subject: Re: [R] Rolling 7 day incidence
> 
> 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
> [...]
> 
> 
> --
> To email me replace 'nospam' with 'el'
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

R help - Aug 2021 - Rolling 7 day incidence

[R] Rolling 7 day incidence

[R] Rolling 7 day incidence