Hi petr,
Thanks for the reply.
My original data is in comma separated variable (csv) format with variable
names in column 1 and numeric data in the remaining columns. The read.csv
command reads this data set into object name pcrdata as a dataframe where
the variable names and numeric data are
Hi Michael
r-help-boun...@r-project.org napsal dne 18.03.2010 12:02:19:
Hi petr,
Thanks for the reply.
My original data is in comma separated variable (csv) format with
variable
names in column 1 and numeric data in the remaining columns. The
read.csv
command reads this data set into
Hi
as you did not provide data it is hard to say what is wrong.
You can see that it is working on dates similar what you described.
test - data.frame(x=letters[1:10], y=rnorm(10), z=runif(10))
test
x y z
1 a 0.09980806 0.32211567
2 b 0.70559139 0.32204076
3 c
I am currently trying to write a program that minimises the amount of work
required for auditable qPCR data. At the moment I am using an Excel (.csv)
spreadsheet as source data that has been transposed to the column format
required for R to read. Unfortunately, this means I have* *to manually
Hi!
I don't really understand why you do pcrdata-as.data.frame(t(pcrdata))
Do you need to transpose the dataset? Because read.csv() creates a
dataframe already.
Something I found really useful recently is the package xlsReadWrite
where the function read.xls() has an argument colClasses
Why use a csv dataset as an intermediary? Use RExcel and get
the dataset directly from your Excel source.
See http://rcom.univie.ac.at for full details.
You can download the RExcelInstaller package from CRAN with
install.packages(RExcelInstaller)
library(RExcelInstaller)
installRExcel()
Rich
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