Displaying 20 results from an estimated 6000 matches similar to: "Creating a vector of categories"
2005 Jun 25
1
Confidence interval bars on Lattice barchart with groups
I am trying to add confidence (error) bars to lattice barcharts (and
dotplots, and xyplots). I found this helpful message from Deepayan
Sarkar and based teh code below on it:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/50299.html
However, I can't get it to work with groups, as illustrated. I am sure I
am missing something elementary, but I am unsure what.
Using R 2.1.1 on various
2007 Jun 20
2
"xtable" results doesn't correspond to data.frame
Dear useRs,
Am trying to use xtable on the following data.frame and I don't get what I
expect:
example.table <- data.frame(rbind(
c("Gender"," "," "," "),
cbind(rep(" ",2),c("Male","Female"),c(3.0,4.0),c(3/7,4/7))
))
colnames(example.table) <- c(" "," ","number of
2009 Jan 22
2
Frequency and summary statistics table with different variables and categories
Hello helpers,
This is probably quite simple, but I'm stuck.
I want to create a summary statistics table with frequencies and summary
statistics for a large number of variables. The problem here is that (1)
there are two different classes of categories (sex, type of substance abuse
and type of treatent) which overlap, (2) the data for different variables
should be presented in different
2013 Apr 18
6
count each answer category in each column
Hey,
Is it possible that R can calculate each options under each column and
return a summary table?
Suppose I have a table like this:
Gender Age Rate
Female 0-10 Good
Male 0-10 Good
Female 11-20 Bad
Male 11-20 Bad
Male >20 N/A
I want to have a summary table including the information that how many
answers in each category, sth like this:
X
2023 Nov 04
2
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
I might have factored the gender.
I'm not sure it would in any way be quicker. But might be to some extent
easier to develop variations of. And is sort of what factors should be
doing...
# make dummy data
gender <- c("Male", "Female", "Male", "Female")
WC <- c(70,60,75,65)
TG <- c(0.9, 1.1, 1.2, 1.0)
myDf <- data.frame( gender, WC, TG )
#
2023 Nov 03
2
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Just a minor point in the suggested solution:
df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG))
since WC and TG are not conditional, would this be a slight improvement?
df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58)))
-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via
R-help
Sent: Friday,
2023 Nov 05
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
There are many techniques Callum and yours is an interesting twist I had not considered.
Yes, you can specify what integer a factor uses to represent things but not what I meant. Of course your trick does not work for some other forms of data like real numbers in double format. There is a cost to converting a column to a factor that is recouped best if it speeds things up multiple times.
The
2010 May 01
2
Average Login based on date
Hi All,
I have the data like this :
>sample <- read.csv(file="sample.csv",sep=",",header=TRUE)
> sample
stdate Domain sex age Login
1 01/11/09 xxx FeMale 25 2
2 01/11/09 xxx FeMale 35 4
3 01/11/09 xxx Male 18 30
4 01/11/09 xxx Male 31 3
5 02/11/09 xxx Male 32 11
6 02/11/09 xxx Male 31 1
7 02/11/09
2008 Feb 12
3
help with bwplot
Dear list,
I have following data set, which I want to plot the "Scale" variable on the
x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The Mean
value of each Ageclass for each sex would be connected by a line. Totally,
there should be 6 lines, from which three present the Mean values of each
Ageclass for respective sex. Are there any easy ways to do
2005 Dec 24
2
grouping data
Hello R-users/experts,
I am new to R-
I have a simple question:
Let say I have a data set as follows
temp:[file attached]
the data structure is a follows:
sex age
female 28
female 53
female 53
female 36
male 42
male 29
male 43
male 36
male 41
Here we are grouping all male value into male and all female value in to
female
2023 Nov 03
1
[EXTERNAL] RE: I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Yes, that will halve the number of multiplications.
If you?re looking for such optimisations then you can also consider ifelse(G=='male', 65L, 58L). That will definitely use less time & memory if WC is integer, but the trade-offs are more complicated if WC is floating point.
Regards,
Jorgen Harmse.
From: avi.e.gross at gmail.com <avi.e.gross at gmail.com>
Date: Friday,
2010 May 07
2
extract required data from already read data
Hi all,
I have data like this:
>sample <- read.csv(file="sample.csv",sep=",",header=TRUE)
> sample
stdate Domain sex age Login
1 01/11/09 xxx FeMale 25 2
2 01/11/09 xxx FeMale 35 4
3 01/11/09 xxx Male 18 30
4 01/11/09 xxx Male 31 3
5 02/11/09 xxx Male 32 11
6 02/11/09 xxx Male 31 1
7 02/11/09
2008 Nov 17
5
how to calculate another vector based on the data from a combination of two factors
Hi,
I have a data set similar to the following
State Gender Quantity
TX Male 1
NY Female 2
TX Male 3
NY Female 4
I need to calculate cumulative sum of the quantity by State and Gender. The
expected output is
State Gender Quantity CumQuantity
TX Male 1 1
TX Male 3 4
NY Female 2 2
NY Female 4 6
I highly appreciate if someone can give me some hints on solving that in R.
Hao
--
View this
2023 Nov 03
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Hello Everyone,
I have three variables: Waist circumference (WC), serum triglyceride (TG)
level and gender. Waist circumference and serum triglyceride is numeric and
gender (male and female) is categorical. From these three variables, I want
to calculate the "Lipid Accumulation Product (LAP) Index". The equation to
calculate LAP is different for male and females. I am giving both
2009 Mar 17
2
converting null to some values
Hi,
I have newbie question. Suppose I have the following data:
temp <- data.frame(type1 = c("male", "female", "male", "female", "female"),
type2 = c("low", "med", "high", "low", "med"), a = c(1,2,4, NA, 3), b =
.... [TRUNCATED]
temp
type1 type2 a b c
1 male low 1 5 0
2 female
2023 Nov 03
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG))
That will do both calculations and merge the two vectors appropriately. It will use extra memory, but it should be much faster than a 'for' loop.
Regards,
Jorgen Harmse.
------------------------------
Message: 8
Date: Fri, 3 Nov 2023 11:10:49 +1030
From: "Md. Kamruzzaman" <mkzaman.m at gmail.com>
2011 Jan 23
2
Creating subsets of a matrix
Hello,
Say I have 2 columns, bmi and gender, the first being all the values and the
second being male or female. How would I subset this into males only and
females only? I have searched these fora and read endlessly about select[]
and split() functions but to no avail. Also the table is not ordered.
bmi gender -> bmi gender + bmi gender
1 24.78 male
2023 Nov 03
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Well, something like:
LAP <- ifelse(gender =='male', (WC-65)*TG, (WC-58)*TG)
The exact code depends on whether your variables are in a data frame or
list or whatever, which you failed to specify. If so, ?with may be useful.
Cheers,
Bert
On Fri, Nov 3, 2023 at 3:43?AM Md. Kamruzzaman <mkzaman.m at gmail.com> wrote:
> Hello Everyone,
> I have three variables: Waist
2004 Jun 22
1
Grouped AND stacked bar charts possible in R?
Good day all,
My statisticians want an R procedure that will produce grouped stacked
barplots. Barplot will
stack or group, but not both. The ftable function can produce a table
of the exact form they want, but the barplot doesn't show all the
divisions we want.
For an example, here's the sample from the help file for "ftable:"
data(Titanic)
ftable(Titanic, row.vars = 1:3)