I like the approach presented by Jeff Newmiller as shown in the previous
post (I really like his way). As he suggested, it would be good to
start with 'factor' since you have all values of 'Primary.Viol.Type'.
You may try to use 'split()' function for creating table that you wish
to build. Please see the below (I hope this helps):
> PViol.Type.Per.Case.Original$Primary.Viol.Type <-
factor(Primary.Viol.Type, levels=PViol.Type, labels=PViol.Type)
>
> tmp <- split(PViol.Type.Per.Case.Original,
PViol.Type.Per.Case.Original$CaseID)
> ans <- ifelse(do.call(rbind, lapply(tmp, function(x)
table(x$Primary.Viol.Type))), 1, NA)
> ans
CaseID BW.BackWages LD.Liquid_Damages MW.Minimum_Wage OT.Overtime
1005317 NA NA NA NA NA
1007183 NA NA NA NA 1
1008833 NA NA NA NA 1
1012281 NA NA NA NA NA
1015285 NA NA NA NA NA
1015315 NA NA NA NA 1
1015322 NA NA NA NA NA
RK.Records_FLSA V.Poster_Other AS.Age BW.WHMIS_BackWages HS.Hours
1005317 NA NA NA NA 1
1007183 NA NA NA NA NA
1008833 NA NA NA NA NA
1012281 NA NA NA NA 1
1015285 NA 1 1 NA 1
1015315 NA NA NA NA NA
1015322 NA 1 NA NA NA
OA.HazOccupationAg ON.HazOccupationNonAg R3.Reg3AgeOccupation
1005317 NA NA NA
1007183 NA NA NA
1008833 NA NA NA
1012281 NA NA NA
1015285 NA NA NA
1015315 NA NA NA
1015322 NA NA NA
RK.Records_CL V.Other
1005317 NA NA
1007183 NA NA
1008833 NA NA
1012281 NA NA
1015285 1 NA
1015315 NA NA
1015322 NA NA
>
Chel Hee Lee
On 12/18/2014 10:02 AM, Jeff Newmiller wrote:
No guarantees on "best"... but one way using base R could be:
# Note that "CaseID" is actually not a valid PViol.Type as you had it
PViol.Type <- c( "BW.BackWages"
, "LD.Liquid_Damages"
, "MW.Minimum_Wage"
, "OT.Overtime"
, "RK.Records_FLSA"
, "V.Poster_Other"
, "AS.Age"
, "BW.WHMIS_BackWages"
, "HS.Hours"
, "OA.HazOccupationAg"
, "ON.HazOccupationNonAg"
, "R3.Reg3AgeOccupation"
, "RK.Records_CL"
, "V.Other" )
# explicitly specifying all levels to the factor insures a complete
# set of column outputs regardless of what is in the input
PViol.Type.Per.Case.Original <-
data.frame( CaseID
, Primary.Viol.Type=factor( Primary.Viol.Type
, levels=PViol.Type ) )
tmp <- table( PViol.Type.Per.Case.Original )
ans <- data.frame( CaseID=rownames( tmp )
, as.data.frame( ifelse( 0==tmp, NA, 1 ) )
)
On Wed, 17 Dec 2014, bcrombie wrote:
# I have a dataframe that contains 2 columns:
CaseID <- c('1015285',
'1005317',
'1012281',
'1015285',
'1015285',
'1007183',
'1008833',
'1015315',
'1015322',
'1015285')
Primary.Viol.Type <- c('AS.Age',
'HS.Hours',
'HS.Hours',
'HS.Hours',
'RK.Records_CL',
'OT.Overtime',
'OT.Overtime',
'OT.Overtime',
'V.Poster_Other',
'V.Poster_Other')
PViol.Type.Per.Case.Original <- data.frame(CaseID,Primary.Viol.Type)
# CaseID?s can be repeated because there can be up to 14
Primary.Viol.Type?s
per CaseID.
# I want to transform this dataframe into one that has 15 columns,
where the
first column is CaseID, and the rest are the 14 primary viol. types. The
CaseID column will contain a list of the unique CaseID?s (no
replicates) and
for each of their rows, there will be a ?1? under a column
corresponding to
a primary violation type recorded for that CaseID. So, technically,
there
could be zero to 14 ?1?s? in a CaseID?s row.
# For example, the row for CaseID '1015285' above would have a ?1? under
?AS.Age?, ?HS.Hours?, ?RK.Records_CL?, and ?V.Poster_Other?, but have
"NA"
under the rest of the columns.
PViol.Type <- c("CaseID",
"BW.BackWages",
"LD.Liquid_Damages",
"MW.Minimum_Wage",
"OT.Overtime",
"RK.Records_FLSA",
"V.Poster_Other",
"AS.Age",
"BW.WHMIS_BackWages",
"HS.Hours",
"OA.HazOccupationAg",
"ON.HazOccupationNonAg",
"R3.Reg3AgeOccupation",
"RK.Records_CL",
"V.Other")
PViol.Type.Columns <- t(data.frame(PViol.Type)
# What is the best way to do this in R?
--
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and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@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.
