[R] a simple reshape

Rui Barradas ru|pb@rr@d@@ @end|ng |rom @@po@pt
Fri Apr 3 23:30:07 CEST 2020


Hello,

That function is new (tidyr 1.0.0) and exists in

packageVersion('tidyverse')
#[1] ‘1.3.0’
packageVersion('tidyr')
#[1] ‘1.0.2’

 From the help page ?pivot_wider:

Details

pivot_wider() is an updated approach to spread(), designed to be both 
simpler to use and to handle more use cases. We recommend you use 
pivot_wider() for new code; spread() isn't going away but is no longer 
under active development.


So you must update your packages.

Hope this helps,

Rui Barradas


Às 20:17 de 03/04/20, Yuan Chun Ding escreveu:
> Hi Rui,
> 
> Thanks a lot,
> 
> i got this error, I have library(tidyverse).
> 
> Ding
> 
>   Error in pivot_wider(., id_cols = "vntr1", names_from = "group", names_prefix = "a",  :
>    could not find function "pivot_wider"
> ________________________________________
> From: Rui Barradas [ruipbarradas using sapo.pt]
> Sent: Friday, April 3, 2020 12:08 PM
> To: Yuan Chun Ding; r-help mailing list
> Subject: Re: [R] a simple reshape
> 
> Hello,
> 
> It's a bit more complicated than you have coded it.
> I will use pivot_wider, it's now the natural way of doing it.
> 
> 
> test1 %>%
>     group_by(vntr1) %>%
>     mutate(group = row_number()) %>%
>     ungroup() %>%
>     pivot_wider(
>       id_cols ="vntr1",
>       names_from = "group",
>       names_prefix = "a",
>       values_from = "val"
>     )
> 
> 
> Hope this helps,
> 
> Rui Barradas
> 
> Às 19:57 de 03/04/20, Yuan Chun Ding escreveu:
>> Hi R users,
>>
>> I want to do a data reshape from long to wide, I thought it was easy using tidyverse spread function, but it did not work well. Can you help me?
>>
>> Thank you,
>>
>> Ding
>>
>> test1 data frame is long file and test2 is the wide file I want to get
>>
>> test1 <- data.frame (vntr1=c("v1","v1", "v2","v2","v2","v2"),
>>                        val =c(0.98,0.02, 0.59,0.12,0.11,0.04))
>>
>> test2  <- data.frame(vntr1=c("v1","v2"),
>>                        a1 =c(0.98, 0.5693),
>>                        a2 = c(0.02, 0.12),
>>                        a3 =c(NA, 0.11),
>>                        a4=c(NA, 0.04))
>>
>> the following code does not work
>> test2 <-test1 %>%spread(vntr1, val)
>>
>>    Error: Each row of output must be identified by a unique combination of keys.
>> Keys are shared for 6 rows:
>> * 1, 2
>> * 3, 4, 5, 6
>> Do you need to create unique ID with tibble::rowid_to_column()?
>> Call `rlang::last_error()` to see a backtrace
>>
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