I'm currently struggling with creating a nice output file for performed regressions.
I stored all my performed regressions (25) with the lm function in a list. It is very inconvenient to analyze the output in R (at least i don't know how to do it efficiently). For that reason I d like to export all my results in an Excel Sheet.
The list called "myregressions" has 25 entries of the 25 regressions which are named after the performed year : myregression$year_1988 - myregression$year_2011 with all the information on coefficients, residuals, effects rank etc.
Is there an easy way to accomplish that? Thank you all in advance.
You could convert the list into a data frame, and then do something like this:
dataFrameToCSV = function(dataFrame, path)
{
write.table(dataFrame, path, sep=",", row.names=FALSE)
}
Related
I almost finish a messy code to apply several statistical methods/test to 11 data frames from different watersheds with physico-chemical parameters as variables. I reach the goal, but I need to do this functional.
So to start i made a function to compute correlation, and save the results as .txt tables and .pdf images.
It works great when run the function to one dataframe at the time (for that you should import each dataframe separately using read.table, which is not written in the code below).
As i want it functional, made a list of the 11 dataframes and use lapply to run the function to each one. It works in the sense that gives me one list (corr) containing the correlation results of each dataframe.
Here comes the issues:
The list cor with correlation results for each dataframe looks like has values instead of data frames, so i dont know how to access or save them (see the corr list in the Environment/Data window). Well, until here, at least looks like correlation results exists somewhere.
The second problem is that when i run corr<-lapply(PQ_data, cor_PQ), which has a line to save the outputs as tables (.txt) and images (.pdf) using part of the name of the original dataframe computed (e.g first element of PQ_data is "AgIX_E_PQ" so table and plot of cor_PQ(PQ_data[["AgIX_E_PQ"]] should get the names "mCorAgIX_E_PQ.txt" and "CorAgIX_E_PQ.pdf" respectively), im getting just one output (mCorX[[I]].txt and CorX[[i]].pdf) with the last dataframe correlation result. That is, tables and images for each dataframe correlation result are overwritten into this generics mCorX[[I]].txt, CorX[[i]].pdf files.
Now i guess have to define 'i' or something to avoid this. Should i define cor_PQ function for PQ_data instead X?
If anyone can see where im failing, i will appreciate any help to solve this, please.
My data: PQ_data /save it in your workspace and fix setwd with it.
My code:
rm(list=ls(all=TRUE))
cat("\014")
setwd("C:/Users/Sol/Documents/ProyectoTítulo/CalidadAgua/Matrices/Regs") #my workspace
PQ_files<-list.files(path="C:/Users/Sol/Documents/ProyectoTítulo/CalidadAgua/Matrices/Regs",
pattern="\\_PQ.txt") #my list of 14 dataframes in my workspace.
PQ_data<-lapply(PQ_files, read.table) #read tables of the 14 dataframes in the list.
names(PQ_data)<-gsub("\\_PQ.txt","", PQ_files) #name the 14 dataframes with their original names.
#FUNCTION TO COMPUTE CORRELATIONS, SAVE TABLES AND PLOTS.
cor_PQ<-function(X) {
corPQ<-cor(X, use="pairwise.complete.obs")
outputname.txt<-paste0("mCor",deparse(substitute(X)),".txt")
write.table(corPQ, file=outputname.txt)
outputname.pdf<-paste0("Cor",deparse(substitute(X)),".pdf")
pdf(outputname.pdf)
plot(X)
dev.off()
return(corPQ)
}
corr<-lapply(PQ_data, cor_PQ)
After this, as i said, a get a list called "corr" with 11 elements containing correlation results from each dataframe in my list (PQ_data), but i cant access them as tables when i pin the "corr" list in my environment/data window (they dont show the blue R arrow to expand the element).
`
And i get only 2 output files called mCorX[[I]].txt and CorX[[i]].pdf showing only the last dataframe correlation result because the write.table and .pdf functions overwrite the results of the 10 previous calculations.
Again, i will appreciate any help. I really need a push to catch the idea.
Thanks!!!
lapply doesn't send names of the list to the function. So although the function works for individual files it doesn't work with list of files. Also since there are no names to the files all the files generated are given the same name, hence all the new files overwrite the previously existing files and in the end you get output with only 1 file which is the last element in your list. You can use the below function where we send the names as different parameter to assign the name to the files.
cor_PQ<-function(X, Y) {
corPQ<-cor(X, use="pairwise.complete.obs")
outputname.txt<-paste0("mCor",Y,".txt")
write.table(corPQ, file= outputname.txt)
outputname.pdf<-paste0("Cor",Y,".pdf")
pdf(outputname.pdf)
plot(X)
dev.off()
return(corPQ)
}
Now use Map to apply the same function.
Map(cor_PQ, PQ_data, names(PQ_data))
We can also use imap from purrr to apply this function.
purrr::imap(PQ_data, cor_PQ)
I'm new to R am trying reorganise my data based on the sampleID
I've used the split() function in R which has does exactly what I wanted it to and stored my information in new data.frames
My question is now that they are in separate data.frames how do I access them individually for further processing?
My code goes as follows
splitList.list = list()
for (i in 1:31)
{
splitList.list[[i]] = split(chromList.list[[i]], chromList.list[[i]]$sampleID)
}
splitList.list[[1]]
I take the files I have (31 files), split them and store them in a list. This much works. I get an output that looks like this
This can be repeated with any of list elements and work. I now what to do some processing on separately on each data.frame but don't know how to access just one of these. Please help
im super newbie on R and i have been learning for myself for a few weeks already due my work degree.
Im almost done with the statistical analysis that i need, but it is through an ugly and messy code, that is, repeating lot of codes for several data frames, to apply different statistical tests, save results, etc.
Well now, for personal interest, want to write this better, but im totally trapped in my ignorance and really need a push to get the idea, please.
For example, i want to create a function that measure the correlation on all the data tables im using and save those results as a tables using the input name as part of the output name.
I mean, if we had the iris data but measured on different seasons, e.g. iris_fall, iris_winter, iris_spring and iris_summer, after apply cor(X) method to each one, i want to save those results as tables called like "mCoriris_fall.txt", "mCoriris_winter.txt", "mCoriris_spring.txt" and "mCoriris_summer.txt" respectively.
My useless code for now say:
cor_PQ<-function(X) {
cor_PQ<-cor(X, use="pairwise.complete.obs")
return(cor_PQ)
}
savecor<-function(t) {
outputname<-(paste0("mCor",t)) #HOW DO I CALL THE NAME OF THE INPUT? t is cor_PQ result matrix.
savecor<-write.table(t, file=paste0(outputname,".txt"))
return(savecor)
}
cor_PQ(Iris_fall)
I expect to get cor result and save it as a table in my workspace, using the input name as part of the output name.
Im aware this are 2 separates functions and the one to write table should be inside the function for cor(x), but i cant understand how.
I have been reading a lot but i just cant fit all in my head.
Thanks to anyone who can help me.
Regards.
UNTIL HERE IT HAS BEEN SOLVED...
But after making a list with my 14 data frames to apply cor and other methods, the write.table function overwrite the 14 cor results on 1 single doc. This is my code.
PQ_files<-list.files(path="C:/Users/Sol/Documents/ProyectoTítulo/CalidadAgua/Matrices/Regs",pattern="\\_PQ.txt")
PQ_data<-lapply(PQ_files, read.table)
names(PQ_data)<-gsub("\\_PQ.txt","", PQ_files)
PQ_data
cor_PQ<-function(X) {
cor_PQ<-cor(X, use="pairwise.complete.obs")
outputname.txt<-paste0("mCor",deparse(substitute(X)),".txt")
write.table(cor_PQ, file=outputname.txt)
outputname.pdf<-paste0("Cor",deparse(substitute(X)),".pdf")
pdf(outputname.pdf)
plot(X)
dev.off()
return(cor_PQ)
}
for (i in seq_along(PQ_data)){
Correlaciones<-lapply(PQ_data,cor_PQ)
}
Correlaciones
On SUM: seems to work almost good, until the write.table and plot(x) overwrite the outputs from the 14 dataframes on my PQ_data withe the name mCor[[i]] and CorX[[i]], respectively.
Should i define [i] somehow to have each results with the right name?
Also, when i run Correlaciones at the end, i can see the cor result for the 14 dataframes in one single dataframe, but i dont know how to split them correctly.
I guess almost there.
THANKS AGAIN!
You can combine the two functions and use deparse substitute to get input names as string
cor_PQ <- function(X) {
cor_PQ<-cor(X, use="pairwise.complete.obs")
outputname<- paste0("mCor",deparse(substitute(X)), ".txt")
write.table(t, file=outputname)
return(cor_PQ)
}
and then call
cor_PQ(Iris_fall)
I have multiple csv-files in one folder. I want to load each csv-file in this folder into one separate data frame. Next, I want to extract certain elements from this data frame into a matrix and calculate the mean of all these matrixes.
setwd("D:\\data")
group_1<-list.files()
a<-length(group_1)
mferg_mean<-data.frame
for(i in 1:a)
{
assign(paste0("mferg_",i),read.csv(group_1[i],header=FALSE,sep=";",quote="",dec=",",col.names=1:90))
}
As there are 11 csv-files in the folder I now have the data frames
mferg_1
to
mferg_11
How can I address each data frame in this loop? As mentioned, I want to extract certain elements from each data frame to a matrix. I would imagine it something like this:
assign(paste0("mferg_matrix_",i),mferg_i[1:5,1:10])
But this obviously does not work because R does not recognize mferg_i in the loop. How can I address this data frame?
This is not something you should probably be using assign for in the first place. Working with a bunch of different data.frames in R is a mess, but working with a list of data.frames is much easier. Try reading your data with
group_1<-list.files()
mferg <- lapply(group_1, function(filename) {
read.csv(filename,header=FALSE,sep=";",quote="",dec=",",col.names=1:90))
})
and you get each each value with mferg[[1]], mferg[[1]], etc. And then you can create a list of extractions with
mferg_matrix <- lapply(mferg, function(x) x[1:5, 1:10])
This is the more R-like way to do things.
But technically you can use get to retrieve values like you use assign to create them. For example
assign(paste0("mferg_matrix_",i),get(paste0("mferg_",i))[1:5,1:10])
but again, this is probably not a smart strategy in the long run.
Maybe someone here with more expirience with mcmc objects can help me out.
Problem: I have a list with 20+ mcmc objects stored. I need to assign variable names for each of the mcmc object.
I have another list with all the variables names for each mcmc stored (as columns in dataframes).
I can do this individually, using the "varnames" function from the coda package, like this:
Being "votes" my dataframe list and "posterior" my mcmc object list..
names <- votes[[1]]$legis # extracts the names variable for the first dataframe on the list.
varnames(posterior[[1]]) <- names # assings the extracted names as variable names fo the first mcmc object on the list.
However, rather than doing this one by one, I would like to do it all at once. I've tried the following code...
p2 <- lapply(posterior, function(x)varnames(posterior[[x]]) <- names)
But i get Error in *tmp*[[x]] : Recursive indexing failed at level 2 . I've tried some variations of that line, but I'm having a hard time understanding how to properly index this, or how to do what I want to do at all.
I know its kind of an specific problem, but maybe someone here can give me a hint or something.
Thanks in advance for the help. Sorry I can't provide some data, but it's kinda difficult to get workable samples of this.
Regards,
Federico
You don't need to do any lapply.
try names(posterior) <- votes[[1]]$legis