Say your dataframe is named prb.df:
oldnames<-names(prb.df)
ncol<-ncols(prb.df)
names(prb.df)<-paste0("Q",1:ncol)
barplot(...,names.arg=oldnames,...)
Jim
On Fri, Nov 2, 2018 at 1:56 AM P. Roberto Bakker
<robertobak...@gmail.com> wrote:
>
> Yes, that is an good idea, only then I loose the original column lables which
> I need in my barplot. Isn't it?
>
> Op do 1 nov. 2018 om 11:03 schreef Jim Lemon <drjimle...@gmail.com>:
>>
>> I would use the "names" or "colnames" functions to change them to Q1,
>> Q2, ... as I did.
>>
>> Jim
>>
>> On Thu, Nov 1, 2018 at 9:01 PM P. Roberto Bakker
>> <robertobak...@gmail.com> wrote:
>> >
>> > Hi Jim,
>> >
>> > Thank you for your quick reply. It is a great procedure.
>> > The response options in my data.frame are (fortunately) similar in all
>> > columns.
>> > It would be nice if I could use your procedure in all columns at once
>> > instead of each column.
>> > My data.frame contains 48 columns, each with long column names.
>> > This means that I need to put each (long) column name after "$:
>> > dataname$"very long name".
>> > So, is ther a way to do this procedure for all columns?
>> >
>> > Roberto
>> >
>> >
>> > Op do 1 nov. 2018 om 10:50 schreef Jim Lemon <drjimle...@gmail.com>:
>> >>
>> >> Hi Roberto,
>> >> What I suggested is a brute force method of translating response
>> >> options into ordinal numbers. Fortunately for me, the Barratt
>> >> Impulsivity Scale has relatively short and constant response options.
>> >> As I programmed the test myself, I already had the questions in plain
>> >> text, so I simply added the "as.numeric(factor(" and "levels=..."
>> >> commands to the forward and reversed response options to create the
>> >> whole transformation code. With a bit of cut-and-paste work, it didn't
>> >> take that long. Because the BIS-11 is used quite a bit where I am
>> >> working. it was worth the trouble.
>> >>
>> >> Jim
>> >>
>> >> On Thu, Nov 1, 2018 at 8:38 PM P. Roberto Bakker
>> >> <robertobak...@gmail.com> wrote:
>> >> >
>> >> > Hi Jim,
>> >> >
>> >> > Thank you.
>> >> > An additional question: as I have many columns to change in numeric,
>> >> > and the columns are long sentences, what is an efficient way to do this?
>> >> > I checked in StackOverflow but could not find the right answer
>> >> > Best Roberto
>> >> >
>> >> >
>> >> > Op do 1 nov. 2018 om 00:25 schreef Jim Lemon <drjimle...@gmail.com>:
>> >> >>
>> >> >> Hi Roberto,
>> >> >> Here is a snippet of code that translates the text responses of the
>> >> >> BIS-11 into numeric values. Note the reversal of the order in the
>> >> >> second item:
>> >> >>
>> >> >> BIS$Q1<-as.numeric(factor(BIS$Q1,
>> >> >> levels=c("Almost","Often","Occasionally","Rarely/Never")))
>> >> >> BIS$Q2<-as.numeric(factor(BIS$Q2,
>> >> >> levels=c("Rarely/Never","Occasionally","Often","Almost")))
>> >> >> ...
>> >> >>
>> >> >> Jim
>> >> >> On Thu, Nov 1, 2018 at 8:57 AM P. Roberto Bakker
>> >> >> <robertobak...@gmail.com> wrote:
>> >> >> >
>> >> >> > Hi Rich,
>> >> >> >
>> >> >> > Thank you for your answer.
>> >> >> > The sentences are strings (likert scale: 'the situation is highly
>> >> >> > applicable to me' etc - in Dutch), or column labels; it may be
>> >> >> > confusing as
>> >> >> > it is in Dutch. Below I show you part of the dataframe with my
>> >> >> > annotation
>> >> >> > added (string/column lable) to give you an idea.
>> >> >> > I need to change the likert strings into numeric (1:5). And this is a
>> >> >> > challenge somehow.
>> >> >> > With dplyr, plyr it did not work.
>> >> >> > After I have the numeric version then I can stack them as suggested
>> >> >> > by
>> >> >> > David.
>> >> >> >
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