[R] cleanup/replacing a value on condition of another value

[Rui Barradas]

Hello,

The following works with me.


library(coronavirus)
library(dplyr)

data(coronavirus, package = "coronavirus")
#update_dataset(silence = FALSE)

coronavirus %>%
   select(country, date, type, cases) %>%
   filter(
     country == 'Namibia',
     date == '2021-10-23',
     cases == 357
   )



Can you post the pipe code you are running?

Hope this helps,

Rui Barradas

Às 12:25 de 25/10/21, Dr Eberhard W Lisse escreveu:
> Hi,
> 
> I have data from JHU via the 'coronavirus' package which has a value for
> the confirmed cases for 2021-10-23 which differs drastically (357) from
> what is reported in country (23).
> 
>      # A tibble: 962 × 4
>        country date       type      cases
>        <chr>   <date>     <chr>     <int>
>      1 Namibia 2021-10-24 confirmed    23
>      2 Namibia 2021-10-24 death         4
>      3 Namibia 2021-10-23 confirmed   357
>      4 Namibia 2021-10-23 death         1
>      5 Namibia 2021-10-22 confirmed    30
>      6 Namibia 2021-10-22 death         1
>      # … with 956 more rows
> 
> I am using a '%>%' pipeline and am struggling to mutate 'cases' to NA
> using something like
> 
>      country == 'Namibia' & date == '2021-10-23' & cases == 357
> 
> so that if or when the data-set is corrected I don't have to change the
> code (immediately), even after some googling.
> 
> I can do
> 
>      cases == 357
> 
> only, but that could find other cases as well, which is obviously not 
> the thing to do
> 
> Any suggestions?
> 
> greetings, el
> 
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