It would help if you provided an example for your data frame, and example
for your spreadsheet, and more information on how to judge if the ppm
values "are similar". Maybe this code will help you get started ...
# Here's an example data frame
mydf <- data.frame(
compound=letters[1:10],
ppm=abs(round(rnorm(10), 4)),
frequency=abs(round(rnorm(10), 4)))
# Here's an example data frame representing data from your spreadsheet
# You can read the data from the spreadsheet into R using the package
XLConnect
# library(XLConnect)
# mysheet <- readWorksheet(loadWorkbook("C:\\Temp\\Compounds.xlsx"),
sheet="Sheet1", startRow=1)
mysheet <- data.frame(
compound=letters[sample(1:10, 100, replace=TRUE)],
libppm=abs(round(rnorm(100), 4)))
# combine the two example data frames
both <- merge(mydf, mysheet)
# list the compounds in mydf that had ppm values within 0.1 of those in
the spreadsheet
both$diff <- abs(both$ppm-both$libppm)
both[both$diff<0.1, ]
Jean
sathya7priya <sathya7pr...@gmail.com> wrote on 06/26/2012 03:34:22 AM:
> I have a data frame consisting of three columns(name of compund,ppm and
> frequency).Name contains string values .ppm and frequency contains
numeric
> values with decimal points upto four digits.
> I have an excel sheet which is like a library.The first column contains
the
> name of compounds and remaining column contains the ppm values of the
> compound which satisfy certain rules.The number of ppm values varies for
> each compound from 4 to 700.
> I need to compare the values of ppm from the dataframe and compare it
with
> the ppm values in excel sheet and give the result if they are similar.
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