Re: [R] Contingency tables from data.frames
The final version with the help of Gabor Grotendieck (thanks Gabor, very much!)
###
# EasieR - Package #
###
# Common function
er.make.table - function(x,
start,
end,
h,
right) {
# Absolut frequency
f - table(cut(x, br=seq(start, end, h), right=right))
# Relative frequency
fr - f/length(x)
# Relative frequency, %
frP - 100*(f/length(x))
# Cumulative frequency
fac - cumsum(f)
# Cumulative frequency, %
facP - 100*(cumsum(f/length(x)))
fi - round(f, 2)
fr - round(as.numeric(fr), 2)
frP - round(as.numeric(frP), 2)
fac - round(as.numeric(fac), 2)
facP - round(as.numeric(facP),2)
# Make final table
res - data.frame(fi, fr, frP, fac, facP)
names(res) - c('Class limits', 'fi', 'fr', 'fr(%)', 'fac', 'fac(%)')
return(res)
}
#With Gabor Grotendieck suggestions (thanks Gabor, very much!)
er.table - function(x, ...) UseMethod(er.table)
er.table.default - function(x,
k,
start,
end,
h,
breaks=c('Sturges', 'Scott', 'FD'),
right=FALSE) {
#User define nothing or not 'x' isn't numeric - stop
stopifnot(is.numeric(x))
#User define only 'x'
#(x, {k, start, end, h}, [breaks, right])
if (missing(k) missing(start) missing(end) missing(h) ){
x - na.omit(x)
brk - match.arg(breaks)
switch(brk,
Sturges = k - nclass.Sturges(x),
Scott = k - nclass.scott(x),
FD = k - nclass.FD(x))
tmp - range(x)
start - tmp[1] - abs(tmp[2])/100
end - tmp[2] + abs(tmp[2])/100
R - end-start
h - R/k
}
#User define 'x' and 'k'
#(x, k, {start, end, h}, [breaks, right])
else if (missing(start) missing(end) missing(h)) {
stopifnot(length(k) = 1)
x - na.omit(x)
tmp - range(x)
start - tmp[1] - abs(tmp[2])/100
end - tmp[2] + abs(tmp[2])/100
R - end-start
h - R/abs(k)
}
#User define 'x', 'start' and 'end'
#(x, {k,} start, end, {h,} [breaks, right])
else if (missing(k) missing(h)) {
stopifnot(length(start) = 1, length(end) =1)
x - na.omit(x)
tmp - range(x)
R - end-start
k - sqrt(abs(R))
if (k 5) k - 5 #min value of k
h - R/k
}
#User define 'x', 'start', 'end' and 'h'
#(x, {k,} start, end, h, [breaks, right])
else if (missing(k)) {
stopifnot(length(start) = 1, length(end) = 1, length(h) = 1)
x - na.omit(x)
}
else stop('Error, please, see the function sintax!')
tbl - er.make.table(x, start, end, h, right)
return(tbl)
}
er.table.data.frame - function(df,
k,
breaks=c('Sturges', 'Scott', 'FD'),
right=FALSE) {
stopifnot(is.data.frame(df))
tmpList - list()
logCol - sapply(df, is.numeric)
for (i in 1:ncol(df)) {
if (logCol[i]) {
x - as.matrix(df[ ,i])
x - na.omit(x)
#User define only x and/or 'breaks'
#(x, {k,}[breaks, right])
if (missing(k)) {
brk - match.arg(breaks)
switch(brk,
Sturges = k - nclass.Sturges(x),
Scott = k - nclass.scott(x),
FD = k - nclass.FD(x))
tmp - range(x)
start - tmp[1] - abs(tmp[2])/100
end - tmp[2] + abs(tmp[2])/100
R - end-start
h - R/k
}
#User define 'x' and 'k'
#(x, k,[breaks, right])
else {
tmp - range(x)
start - tmp[1] - abs(tmp[2])/100
end - tmp[2] + abs(tmp[2])/100
R - end-start
h - R/abs(k)
}
tbl - er.make.table(x, start, end, h, right)
tmpList - c(tmpList, list(tbl))
}
}
valCol - logCol[logCol]
names(tmpList) - names(valCol)
return(tmpList)
}
Best,
--
Jose Claudio Faria
Brasil/Bahia/UESC/DCET
Estatistica Experimental/Prof. Adjunto
mails:
[EMAIL PROTECTED]
[EMAIL PROTECTED]
[EMAIL PROTECTED]
tel: 73-3634.2779
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Contingency tables from data.frames
Gabor Grothendieck wrote:
On 5/24/05, Jose Claudio Faria [EMAIL PROTECTED] wrote:
Dear list,
I'm trying to do a set of generic functions do make contingency tables from
data.frames. It is just running nice (I'm learning R), but I think it can be
better.
I would like to filter the data.frame, i.e, eliminate all not numeric variables.
And I don't know how to make it: please, help me.
Below one of the my functions ('er' is a mention to EasieR, because I'm trying
to do a package for myself and the my students):
#2. Tables from data.frames
#2.1---er.table.df.br (User define breaks and right)
er.table.df.br - function(df,
breaks = c('Sturges', 'Scott', 'FD'),
right = FALSE) {
if (is.data.frame(df) != 'TRUE')
stop('need data.frame data')
dim_df - dim(df)
tmpList - list()
for (i in 1:dim_df[2]) {
x - as.matrix(df[ ,i])
x - na.omit(x)
k - switch(breaks[1],
'Sturges' = nclass.Sturges(x),
'Scott' = nclass.scott(x),
'FD' = nclass.FD(x),
stop('breaks' must be 'Sturges', 'Scott' or 'FD'))
tmp - range(x)
classIni - tmp[1] - tmp[2]/100
classEnd - tmp[2] + tmp[2]/100
R- classEnd-classIni
h- R/k
# Absolut frequency
f - table(cut(x, br = seq(classIni, classEnd, h), right = right))
# Relative frequency
fr - f/length(x)
# Relative frequency, %
frP - 100*(f/length(x))
# Cumulative frequency
fac - cumsum(f)
# Cumulative frequency, %
facP - 100*(cumsum(f/length(x)))
fi - round(f, 2)
fr - round(as.numeric(fr), 2)
frP - round(as.numeric(frP), 2)
fac - round(as.numeric(fac), 2)
facP - round(as.numeric(facP),2)
# Table
res - data.frame(fi, fr, frP, fac, facP)
names(res) - c('Class limits', 'fi', 'fr', 'fr(%)', 'fac', 'fac(%)')
tmpList - c(tmpList, list(res))
}
names(tmpList) - names(df)
return(tmpList)
}
To try the function:
#a) runing nice
y1=rnorm(100, 10, 1)
y2=rnorm(100, 58, 4)
y3=rnorm(100, 500, 10)
mydf=data.frame(y1, y2, y3)
#tbdf=er.table.df.br (mydf, breaks = 'Sturges', right=F)
#tbdf=er.table.df.br (mydf, breaks = 'Scott', right=F)
tbdf=er.table.df.br (mydf, breaks = 'FD', right=F)
print(tbdf)
#b) One of the problems
y1=rnorm(100, 10, 1)
y2=rnorm(100, 58, 4)
y3=rnorm(100, 500, 10)
y4=rep(letters[1:10], 10)
mydf=data.frame(y1, y2, y3, y4)
tbdf=er.table.df.br (mydf, breaks = 'Scott', right=F)
print(tbdf)
Try this:
sapply(my.data.frame, is.numeric)
Also you might want to look up:
?match.arg
?stopifnot
?ncol
?sapply
?lapply
Thanks Gabor, you suggestion solve my basic problem.
I'm working is same basic (but I think useful) functions
for begginiers.
Below you can see the set of functions:
###
# EasyeR - Package #
###
# Common function---
er.make.table - function(x,
classIni,
classEnd,
h,
right) {
# Absolut frequency
f - table(cut(x, br = seq(classIni, classEnd, h), right = right))
# Relative frequency
fr - f/length(x)
# Relative frequency, %
frP - 100*(f/length(x))
# Cumulative frequency
fac - cumsum(f)
# Cumulative frequency, %
facP - 100*(cumsum(f/length(x)))
fi - round(f, 2)
fr - round(as.numeric(fr), 2)
frP - round(as.numeric(frP), 2)
fac - round(as.numeric(fac), 2)
facP - round(as.numeric(facP),2)
# Table
res - data.frame(fi, fr, frP, fac, facP)
names(res) - c('Class limits', 'fi', 'fr', 'fr(%)', 'fac', 'fac(%)')
return(res)
}
#1. Tables from vectors
#1.1---er.table.br (User define breaks and right)---
er.table.br - function(x,
breaks = c('Sturges', 'Scott', 'FD'),
right = FALSE) {
if (is.factor(x) || mode(x) != 'numeric') stop('need numeric data')
x - na.omit(x)
k - switch(breaks[1],
'Sturges' = nclass.Sturges(x),
'Scott' = nclass.scott(x),
'FD' = nclass.FD(x),
stop('breaks' must be 'Sturges', 'Scott' or 'FD'))
tmp - range(x)
classIni - tmp[1] - abs(tmp[2])/100
classEnd - tmp[2] + abs(tmp[2])/100
R- classEnd-classIni
h- R/k
tbl - er.make.table(x, classIni, classEnd, h, right)
return(tbl)
}
#1.2---er.table.kr (User define the class number (k) and right)-
er.table.kr - function(x,
k,
right = FALSE) {
if (is.factor(x) || mode(x) != 'numeric') stop('need numeric data')
if ((k == '') || (k == ' ')) stop('k not defined')
x - na.omit(x)
tmp - range(x)
classIni - tmp[1] - abs(tmp[2])/100
classEnd - tmp[2] + abs(tmp[2])/100
R- classEnd-classIni
h- R/k
tbl - er.make.table(x, classIni, classEnd, h, right)
[R] Contingency tables from data.frames
Dear list,
I'm trying to do a set of generic functions do make contingency tables from
data.frames. It is just running nice (I'm learning R), but I think it can be
better.
I would like to filter the data.frame, i.e, eliminate all not numeric variables.
And I don't know how to make it: please, help me.
Below one of the my functions ('er' is a mention to EasieR, because I'm trying
to do a package for myself and the my students):
#2. Tables from data.frames
#2.1---er.table.df.br (User define breaks and right)
er.table.df.br - function(df,
breaks = c('Sturges', 'Scott', 'FD'),
right = FALSE) {
if (is.data.frame(df) != 'TRUE')
stop('need data.frame data')
dim_df - dim(df)
tmpList - list()
for (i in 1:dim_df[2]) {
x - as.matrix(df[ ,i])
x - na.omit(x)
k - switch(breaks[1],
'Sturges' = nclass.Sturges(x),
'Scott' = nclass.scott(x),
'FD' = nclass.FD(x),
stop('breaks' must be 'Sturges', 'Scott' or 'FD'))
tmp - range(x)
classIni - tmp[1] - tmp[2]/100
classEnd - tmp[2] + tmp[2]/100
R- classEnd-classIni
h- R/k
# Absolut frequency
f - table(cut(x, br = seq(classIni, classEnd, h), right = right))
# Relative frequency
fr - f/length(x)
# Relative frequency, %
frP - 100*(f/length(x))
# Cumulative frequency
fac - cumsum(f)
# Cumulative frequency, %
facP - 100*(cumsum(f/length(x)))
fi - round(f, 2)
fr - round(as.numeric(fr), 2)
frP - round(as.numeric(frP), 2)
fac - round(as.numeric(fac), 2)
facP - round(as.numeric(facP),2)
# Table
res - data.frame(fi, fr, frP, fac, facP)
names(res) - c('Class limits', 'fi', 'fr', 'fr(%)', 'fac', 'fac(%)')
tmpList - c(tmpList, list(res))
}
names(tmpList) - names(df)
return(tmpList)
}
To try the function:
#a) runing nice
y1=rnorm(100, 10, 1)
y2=rnorm(100, 58, 4)
y3=rnorm(100, 500, 10)
mydf=data.frame(y1, y2, y3)
#tbdf=er.table.df.br (mydf, breaks = 'Sturges', right=F)
#tbdf=er.table.df.br (mydf, breaks = 'Scott', right=F)
tbdf=er.table.df.br (mydf, breaks = 'FD', right=F)
print(tbdf)
#b) One of the problems
y1=rnorm(100, 10, 1)
y2=rnorm(100, 58, 4)
y3=rnorm(100, 500, 10)
y4=rep(letters[1:10], 10)
mydf=data.frame(y1, y2, y3, y4)
tbdf=er.table.df.br (mydf, breaks = 'Scott', right=F)
print(tbdf)
Could anyone give me a hint how to work around this?
PS: Excuse my bad English ;-)
--
Jose Claudio Faria
Brasil/Bahia/UESC/DCET
Estatistica Experimental/Prof. Adjunto
mails:
[EMAIL PROTECTED]
[EMAIL PROTECTED]
[EMAIL PROTECTED]
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Contingency tables from data.frames
On 5/24/05, Jose Claudio Faria [EMAIL PROTECTED] wrote:
Dear list,
I'm trying to do a set of generic functions do make contingency tables from
data.frames. It is just running nice (I'm learning R), but I think it can be
better.
I would like to filter the data.frame, i.e, eliminate all not numeric
variables.
And I don't know how to make it: please, help me.
Below one of the my functions ('er' is a mention to EasieR, because I'm trying
to do a package for myself and the my students):
#2. Tables from data.frames
#2.1---er.table.df.br (User define breaks and right)
er.table.df.br - function(df,
breaks = c('Sturges', 'Scott', 'FD'),
right = FALSE) {
if (is.data.frame(df) != 'TRUE')
stop('need data.frame data')
dim_df - dim(df)
tmpList - list()
for (i in 1:dim_df[2]) {
x - as.matrix(df[ ,i])
x - na.omit(x)
k - switch(breaks[1],
'Sturges' = nclass.Sturges(x),
'Scott' = nclass.scott(x),
'FD' = nclass.FD(x),
stop('breaks' must be 'Sturges', 'Scott' or 'FD'))
tmp - range(x)
classIni - tmp[1] - tmp[2]/100
classEnd - tmp[2] + tmp[2]/100
R- classEnd-classIni
h- R/k
# Absolut frequency
f - table(cut(x, br = seq(classIni, classEnd, h), right = right))
# Relative frequency
fr - f/length(x)
# Relative frequency, %
frP - 100*(f/length(x))
# Cumulative frequency
fac - cumsum(f)
# Cumulative frequency, %
facP - 100*(cumsum(f/length(x)))
fi - round(f, 2)
fr - round(as.numeric(fr), 2)
frP - round(as.numeric(frP), 2)
fac - round(as.numeric(fac), 2)
facP - round(as.numeric(facP),2)
# Table
res - data.frame(fi, fr, frP, fac, facP)
names(res) - c('Class limits', 'fi', 'fr', 'fr(%)', 'fac', 'fac(%)')
tmpList - c(tmpList, list(res))
}
names(tmpList) - names(df)
return(tmpList)
}
To try the function:
#a) runing nice
y1=rnorm(100, 10, 1)
y2=rnorm(100, 58, 4)
y3=rnorm(100, 500, 10)
mydf=data.frame(y1, y2, y3)
#tbdf=er.table.df.br (mydf, breaks = 'Sturges', right=F)
#tbdf=er.table.df.br (mydf, breaks = 'Scott', right=F)
tbdf=er.table.df.br (mydf, breaks = 'FD', right=F)
print(tbdf)
#b) One of the problems
y1=rnorm(100, 10, 1)
y2=rnorm(100, 58, 4)
y3=rnorm(100, 500, 10)
y4=rep(letters[1:10], 10)
mydf=data.frame(y1, y2, y3, y4)
tbdf=er.table.df.br (mydf, breaks = 'Scott', right=F)
print(tbdf)
Try this:
sapply(my.data.frame, is.numeric)
Also you might want to look up:
?match.arg
?stopifnot
?ncol
?sapply
?lapply
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
