Calculate and write Mean and SD for columns in R - r

Question

I'm currently working with data in a *csv. I've got an effective script to plot my data already, but I'm stumped by what seems to be the simplest task. I'm trying to write a script that takes my data (arranged in columns) and have it calculate the mean by column and write it to a new document(./testAVG).
Also, I'm trying to take the same data, calculate the SD (by column) and append that data to the end of the original document (preferably in a repeat for the total number of rows of data I have).
Here's the script I have so far:
#Number of lines with data
Nlines = 5
#Number of lines to skip
Nskip = 0
chem <- read.table("./test.csv", skip=Nskip, sep=",", col.names = c("Sample", "SiO2", "Al2O3", "FeO", "MgO", "CaO", "Na2O", "K2O", "Total", "eSiO2", "eAl2O3", "eFeO", "eMgO", "eCaO", "eNa2O", "eK2O"), fill=TRUE, header = TRUE, nrow=Nlines)
sd1 <- sd(chem$SiO2)
sd2 <- sd(chem$Al2O3)
sd3 <- sd(chem$FeO)
sd4 <- sd(chem$MgO)
sd5 <- sd(chem$CaO)
sd6 <- sd(chem$Na2O)
sd7 <- sd(chem$K2O)
avg1 <- colMeans(chem$SiO2, na.rm = FALSE, dims=1)
avg2 <- colMeans(chem$Al2O3, na.rm = FALSE, dims=1)
avg3 <- colMeans(chem$FeO, na.rm = FALSE, dims=1)
avg4 <- colMeans(chem$MgO, na.rm = FALSE, dims=1)
avg5 <- colMeans(chem$CaO, na.rm = FALSE, dims=1)
avg6 <- colMeans(chem$Na2O, na.rm = FALSE, dims=1)
avg7 <- colMeans(chem$K2O, na.rm = FALSE, dims=1)
write <- write.table(sd1,sd2,sd3,sd4,sd5,sd6,sd7, file="./test.csv", append=TRUE, sep=",", dec=".", col.names = c("eSiO2", "eAl2O3", "eFeO", "eMgO", "eCaO", "eNa2O", "eK2O"))
write <- write.table(avg1, avg2, avg3, avg4, avg5, avg6, avg7, file="./testAVG.csv", append=FALSE, sep=",", dec=".", col.names = c("Sample", "SiO2", "Al2O3", "FeO", "MgO", "CaO", "Na2O", "K2O", "Total"))
The data I'm working with is this
Sample, SiO2, Al2O3, FeO, MgO, CaO, Na2O, K2O, Total,eSiO2,eAl2O3,eFeO,eMgO,eCaO,eNa2O,eK2O
01,65.01,14.77,0.34,1.31,17.27,1.14,0.2,100,,,,,,,
02,72.6,16.27,0.53,0.06,1.27,5.55,3.71,100,,,,,,,
03,64.95,14.65,0.18,1.29,17.48,1.21,0.23,100,,,,,,,
04,64.95,14.65,0.18,1.29,17.48,1.21,0.23,100,,,,,,,
I get this error:
Error in colMeans(chem$SiO2, na.rm = FALSE, dims = 1) :
'x' must be an array of at least two dimensions
Any advice? Thanks

Answer 1

The comments already hint at how to do it, but it seems that you are rather new to R, so let me explicitly show you how you could do it better, using the mtcars dataset:
df <- mtcars
df_sd <- apply(df, 2, sd) # this is how to use apply. See ?apply
df_avg <- colMeans(df) # this is how to use colMeans. See ?colMeans
write.table(df_sd, file="test.csv") # no assignment necessary.
write.table(df_avg, file="testAVG.csv") # writing the file is a desired side effect...
Moreover, please consider the following line:
avg1 <- colMeans(chem$SiO2, na.rm = FALSE, dims=1)
The cool thing about colMeans is that it computes the columnwise means for many columns at once. Here, you are supplying only one vector, namely chem$SiO2. If this is really what you want to do, you would just write
avg1 <- mean(chem$SiO2)