[R] Replace NAs in split lists
PIKAL Petr
petr.pikal at precheza.cz
Mon Jan 8 11:29:40 CET 2018
Hi
With the example, na.locf seems to be the easiest way.
> library(zoo)
> na.locf(df1)
ID ID_2 Firist Value
1 a aa TRUE 2
2 a ab FALSE 2
3 a ac FALSE 2
4 b aa TRUE 5
5 b ab FALSE 5
Cheers
Petr
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Jeff
> Newmiller
> Sent: Monday, January 8, 2018 9:13 AM
> To: r-help at r-project.org; Ek Esawi <esawiek at gmail.com>
> Subject: Re: [R] Replace NAs in split lists
>
> Upon closer examination I see that you are not using the split version of
> df1 as I usually would, so here is a reproducible example:
>
> #----
> df1 <- read.table( text=
> "ID ID_2 Firist Value
> 1 a aa TRUE 2
> 2 a ab FALSE NA
> 3 a ac FALSE NA
> 4 b aa TRUE 5
> 5 b ab FALSE NA
> ", header=TRUE, as.is=TRUE )
>
> sdf <- split( df1, df1$ID )
> # note the extra [ 1 ] in case you have more than one non-NA value # per ID
> sdf2 <- lapply( sdf
> , function( z ) {
> z$Value <- ifelse( is.na( z$Value )
> , z$Value[ !is.na( z$Value ) ][ 1 ]
> , z$Value
> )
> z
> }
> )
> df2 <- do.call( rbind, sdf2 )
> df2
> #> ID ID_2 Firist Value
> #> a.1 a aa TRUE 2
> #> a.2 a ab FALSE 2
> #> a.3 a ac FALSE 2
> #> b.4 b aa TRUE 5
> #> b.5 b ab FALSE 5
>
> # or using tidyverse methods
>
> library(dplyr)
> #>
> #> Attaching package: 'dplyr'
> #> The following objects are masked from 'package:stats':
> #>
> #> filter, lag
> #> The following objects are masked from 'package:base':
> #>
> #> intersect, setdiff, setequal, union
> df3 <- ( df1
> %>% group_by( ID )
> %>% do({
> mutate( .
> , Value = ifelse( is.na( Value )
> , Value[ !is.na( Value ) ][ 1 ]
> , Value
> )
> )
> })
> %>% ungroup
> )
> df3
> #> # A tibble: 5 x 4
> #> ID ID_2 Firist Value
> #> <chr> <chr> <lgl> <int>
> #> 1 a aa T 2
> #> 2 a ab F 2
> #> 3 a ac F 2
> #> 4 b aa T 5
> #> 5 b ab F 5
> #----
>
> On Sun, 7 Jan 2018, Jeff Newmiller wrote:
>
> > Why do you want to modify df1?
> >
> > Why not just reassemble the parts as a new data frame and use that
> > going forward in your calculations? That is generally the preferred
> > approach in R so you can re-do your calculations easily if you find a
> > mistake later.
> > --
> > Sent from my phone. Please excuse my brevity.
> >
> > On January 7, 2018 7:35:59 PM PST, Ek Esawi <esawiek at gmail.com> wrote:
> >> I just came up with a solution right after i posted the question, but
> >> i figured there must be a better and shorter one.than my solution
> >> sdf1[[1]][1,4]<-lapplyresults[[1]]
> >> sdf1[[2]][1,4]<-lapplyresults[[2]]
> >>
> >> EK
> >>
> >> On Sun, Jan 7, 2018 at 10:13 PM, Ek Esawi <esawiek at gmail.com> wrote:
> >>> Hi all--
> >>>
> >>> I stumbled on this problem online. I did not like the solution given
> >>> there which was a long UDF. I thought why cannot split and l/s apply
> >>> work here. My aim is to split the data frame, use l/sapply, make
> >>> changes on the split lists and combine the split lists to new data
> >>> frame with the desired changes/output.
> >>>
> >>> The data frame shown below has a column named ID which has 2
> >> variables
> >>> a and b; i want to replace the NAs on the Value column by 2, which
> >>> is the only numeric entry, for ID=a and by 5 for ID=b.
> >>>
> >>> I worked out the solution but could not replace the results in the
> >> split lists.
> >>>
> >>> Original dataframe , df1
> >>> ID ID_2 Firist Value
> >>> 1 a aa TRUE 2
> >>> 2 a ab FALSE NA
> >>> 3 a ac FALSE NA
> >>> 4 b aa TRUE 5
> >>> 5 b ab FALSE NA
> >>> Sdf1
> >>> $a
> >>> ID ID_2 Firist Value
> >>> 1 a aa TRUE 2
> >>> 2 a ab FALSE NA
> >>> 3 a ac FALSE NA
> >>> $b
> >>> ID ID_2 Firist Value
> >>> 4 b aa TRUE 5
> >>> 5 b ab FALSE NA
> >>> Desired results
> >>> ID ID_2 Firist Value
> >>> 1 a aa TRUE 2
> >>> 2 a ab FALSE 2
> >>> 3 a ac FALSE 2
> >>>
> >>> $b
> >>> ID ID_2 Firist Value
> >>> 4 b aa TRUE 5
> >>> 5 b ab FALSE 5
> >>>
> >>> My code
> >>>
> >>> sdf <- split(df1,df$ID)
> >>> lapply(sdf, function(z)
> >> ifelse(is.na(z$Value),z$Value[!is.na(z$Value)],z$Value))
> >>> result:
> >>> $ a: num [1:3] 2 2 2
> >>> $ b: num [1:2] 5 5
> >>>
> >>> How could I put these two lists back in the split data frame, sdf1?
> >>> Then I could use do.call to reassemble a data frame from the split
> >>> lists,
> >>>
> >>> Thanks,
> >>> EK
> >>
> >> ______________________________________________
> >> 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 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.
> >
>
> ---------------------------------------------------------------------------
> Jeff Newmiller The ..... ..... Go Live...
> DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go...
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>
> ______________________________________________
> 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.
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