Hi Jonathan,
What does the following give ?
import sys, rpy2, rpy2.rinterface
print(sys.version_info)
print(rpy2.__version__)
print(rpy2.rinterface.R_VERSION_BUILD)
On 05/07/2013 07:26 PM, Johannah Ryan wrote:
Hi,
I'm pretty new to python and R, and I haven't even done anything
similar (I'm a biologist), so forgive me if this has a trivial solution.
I'm trying to use rpy to make a quick check kind of a tool, to run a
few tests on a column of interest in a spreadsheet against all the
other columns. (I work with large sheets of experimental and clinical
data, we often look for correlations in it as a starting point for
study).
I have code that works in R,and I transliterated it as well as I could
into python according to the documentation.
It seems to me that only ~90 columns are read into r when I do it
through rpy, so I only get graphs for those. It also doesn't like it
when I tell it to look at one of the last columns to compare with the
rest (the first while loop).
Since its entirely possible I'm doing something very basic
incorrectly, here's my whole code. The quoted out bit at the end is
the r code I was basing it on.
there are a few commented out things here and there that I was using
to test different things.
Any additional suggestions would also be appreciated.
ps. I dont think it matters, but just in case, I've been using r from
windows and python from ubuntu.
import rpy2.robjects as rob
r=rob.r
#to quickly compare one column of a spreadsheet to all the other
columns with non paratric tests and graph the results.
r('DATA= read.csv("PLACENTAMERGED.csv",header=T)')
data=r.DATA
needcol=True
while needcol== True:
print "what column are you interested in testing?"
exp=raw_input()
try:
r('y= DATA[, %s]' %exp)
y=r.y
except:
print "Column name not recognized. please type it exactly as
it appears when R reads it"
else:
needcol= False
#exp = "SampleID"
r('y= DATA[, %r]' %exp)
y=r.y
kruskal = rob.r['kruskal.test']
plot=rob.r['plot']
mtext=r['mtext']
sp=r['cor.test']
abline=r['abline']
lm=r['lm']
filename="%stests.txt"%exp
info=open(filename, 'a')
rob.r('names =colnames(DATA)')
names=r.names
pval={}
f=0
for x in names:
rob.r('d <- DATA[, %r]' %x)
d=r.d
try:
result = kruskal(r.y, r.d)
except:
continue
else:
f=f+1
info.write("%s\n%s\n\n\n" %(x, result))
p= float(result[2][0])
if p <= 1:
pval[x]=p
plot(r.d, r.y, xlab=x, ylab=exp)
mtext("k-w test", 1, side=3, adj=1)
mtext(p, side=3, adj=1)
lable='%s%s'%(exp,x)
r('dev.copy(pdf, "%skw.pdf")'%lable)
r('dev.off()')
spval={}
sf=0
for x in names:
rob.r('d <- DATA[, %r]' %x)
d=r.d
try:
result = sp(y, d, method="spearman", exact=False)
except:
continue
else:
sf=sf+1
info.write("%s\n%s\n\n\n" %(x, result))
p= float(result[2][0])
if p <= 1:
spval[x]=p
plot(r.d, r.y, xlab=x, ylab=exp)
r('l= lm(y~d)')
l=r.l
abline(l)
mtext("spearman", 1, side=3, adj=1)
mtext(p, side=3, adj=1)
lable='%s%s'%(exp,x)
r('dev.copy(pdf, "%ssp.pdf")'%lable)
if len(pval) ==0:
print "Nothing is significant by the Kruskal-Wallis test"
else:
print "These groups are significant by the Kruskal-Wallis test"
for x in pval:
print "%s, %f\n" %(x,pval[x])
if len(spval) ==0:
print "Nothing is significant by the Spearman correlation"
else:
print "These groups are significant by the Spearman correlation"
for x in spval:
print "%s, %f\n" %(x,spval[x])
print "done"
"""
DATA<- read.csv("PLACENTAMERGED.csv",header=T)
y=DATA$HME.
#is anything significant?
for(x in colnames(DATA)){
c<-DATA[,x]
result<-try(kruskal.test(y~c, data=DATA));
if(class(result) == "try-error") next;
if(result[3]<.05) {
print(x)
print(result)}
#else print (result[3]
}
print(done)
#test abd graph. categories
for(x in colnames(DATA)){
c<-DATA[,x]
result<-try(kruskal.test(y~c, data=DATA));
if(class(result) == "try-error") next;
print(result)
boxplot(c~y, xlab=x)
mtext( result[3], side=3, adj=1)
}
print(done)
#test and graph continuous
for(x in colnames(DATA)){
c<-DATA[,x]
result<-try(cor.test(y,c,method="spearman", exact=FALSE));
if(class(result) == "try-error") next;
print(result)
summary(c)
sd(c, na.rm=TRUE)
plot(c~y, xlab=x)
abline(lm(y~c))
mtext( result[3], side=3, adj=1)
}
print("done")
"""
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Learn Graph Databases - Download FREE O'Reilly Book
"Graph Databases" is the definitive new guide to graph databases and
their applications. This 200-page book is written by three acclaimed
leaders in the field. The early access version is available now.
Download your free book today! http://p.sf.net/sfu/neotech_d2d_may
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