Sorry about omitting library(plyr).
It's really thanks to Hadley, of course. His contributions make us all (capable
of being) better.
Eric
----- Original message -----
From: Michael Friendly <frien...@yorku.ca>
To: rmail...@justemail.net, r-help@r-project.org
Subject: Re: extracting non-NA entries from a two-way frequency table
Date: Sat, 14 Dec 2013 17:50:00 -0500
Very elegant! Thank you Eric.
(You omitted library(plyr), so I had to search for arrange())
-Michael
On 12/13/2013 3:01 PM, rmail...@justemail.net wrote:
> Perhaps this?
>
> library(reshape2)
> library(stringr)
>
> GeisslerLong <- melt (Geissler, id.vars = c("boys"))
> GeisslerLong <- transform ( GeisslerLong, girls = as.numeric ( str_replace(
> variable, "g", '' )) )
> GeisslerLong <- rename ( GeisslerLong, c( value = "Freq"))
> GeisslerLong <- arrange ( GeisslerLong, boys, girls)
> GeisslerLong <- subset ( GeisslerLong, !is.na ( Freq), select = c( boys,
> girls, Freq))
>
>
> Eric
>
>
> ----- Original message -----
> From: Michael Friendly <frien...@yorku.ca>
> To: "R-help" <r-help@r-project.org>
> Subject: [R] extracting non-NA entries from a two-way frequency table
> Date: Fri, 13 Dec 2013 14:41:58 -0500
>
> I have data in the form of a two-way table recording the number of
> families with varying numbers
> of boys (rows) and girls (columns: g0 -- g12) below, also given in
> dput() format.
>
> I want to convert this to a data frame containing only the non-NA
> entries, with columns
> boys, girls, Freq, where Freq is the table entry. Can anyone help with
> this?
> I suppose that the steps are to transpose each row to a column
> identifying the number of
> girls, and then delete the NAs, but I can't quite see how to do this.
>
>
> > Geissler
> boys g0 g1 g2 g3 g4 g5 g6 g7 g8 g9 g10 g11 g12
> 1 12 7 NA NA NA NA NA NA NA NA NA NA NA NA
> 2 11 24 45 NA NA NA NA NA NA NA NA NA NA NA
> 3 10 30 93 181 NA NA NA NA NA NA NA NA NA NA
> 4 9 90 287 492 478 NA NA NA NA NA NA NA NA NA
> 5 8 264 713 1027 1077 829 NA NA NA NA NA NA NA NA
> 6 7 631 1655 2418 2309 1801 1112 NA NA NA NA NA NA NA
> 7 6 1579 3725 4948 4757 3470 2310 1343 NA NA NA NA NA NA
> 8 5 3666 7908 9547 8498 6436 3878 2161 1033 NA NA NA NA NA
> 9 4 8628 16340 17332 14479 10263 5917 3072 1540 670 NA NA NA NA
> 10 3 20540 31611 30175 22221 13972 7603 3895 1783 837 286 NA NA NA
> 11 2 47819 57179 44793 28630 15700 8171 3951 1776 722 275 104 NA NA
> 12 1 114609 89213 53789 28101 13740 6233 2719 1152 432 151 72 24 NA
> 13 0 NA 108719 42860 17395 7004 2839 1096 436 161 66 30 8 3
>
> Geissler <-
> structure(list(boys = c(12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L,
> 3L, 2L, 1L, 0L), g0 = c(7L, 24L, 30L, 90L, 264L, 631L, 1579L,
> 3666L, 8628L, 20540L, 47819L, 114609L, NA), g1 = c(NA, 45L, 93L,
> 287L, 713L, 1655L, 3725L, 7908L, 16340L, 31611L, 57179L, 89213L,
> 108719L), g2 = c(NA, NA, 181L, 492L, 1027L, 2418L, 4948L, 9547L,
> 17332L, 30175L, 44793L, 53789L, 42860L), g3 = c(NA, NA, NA, 478L,
> 1077L, 2309L, 4757L, 8498L, 14479L, 22221L, 28630L, 28101L, 17395L
> ), g4 = c(NA, NA, NA, NA, 829L, 1801L, 3470L, 6436L, 10263L,
> 13972L, 15700L, 13740L, 7004L), g5 = c(NA, NA, NA, NA, NA, 1112L,
> 2310L, 3878L, 5917L, 7603L, 8171L, 6233L, 2839L), g6 = c(NA,
> NA, NA, NA, NA, NA, 1343L, 2161L, 3072L, 3895L, 3951L, 2719L,
> 1096L), g7 = c(NA, NA, NA, NA, NA, NA, NA, 1033L, 1540L, 1783L,
> 1776L, 1152L, 436L), g8 = c(NA, NA, NA, NA, NA, NA, NA, NA, 670L,
> 837L, 722L, 432L, 161L), g9 = c(NA, NA, NA, NA, NA, NA, NA, NA,
> NA, 286L, 275L, 151L, 66L), g10 = c(NA, NA, NA, NA, NA, NA, NA,
> NA, NA, NA, 104L, 72L, 30L), g11 = c(NA, NA, NA, NA, NA, NA,
> NA, NA, NA, NA, NA, 24L, 8L), g12 = c(NA, NA, NA, NA, NA, NA,
> NA, NA, NA, NA, NA, NA, 3L)), .Names = c("boys", "g0", "g1",
> "g2", "g3", "g4", "g5", "g6", "g7", "g8", "g9", "g10", "g11",
> "g12"), class = "data.frame", row.names = c(NA, -13L))
>
>
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept. & Chair, Quantitative Methods
York University Voice: 416 736-2100 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
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