[R] Replace NAs in split lists

Eric Berger ericjberger at gmail.com
Mon Jan 8 15:41:33 CET 2018


You can enforce these assumptions by sorting on multiple columns, which
leads to

na.locf(df1[ order(df1$ID,df1$Value), ])



On Mon, Jan 8, 2018 at 4:19 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
wrote:

> Yes, you are right if the IDs are always sequentially-adjacent and the
> first non-NA value appears in the first record for each ID.
> --
> Sent from my phone. Please excuse my brevity.
>
> On January 8, 2018 2:29:40 AM PST, PIKAL Petr <petr.pikal at precheza.cz>
> wrote:
> >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...
> >>                                        Live:   OO#.. Dead: OO#..
> >Playing
> >> Research Engineer (Solar/Batteries            O.O#.       #.O#.  with
> >> /Software/Embedded Controllers)               .OO#.       .OO#.
> >rocks...1k
> >>
> >> ______________________________________________
> >> 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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