I'm trying to write out an R output to a text file that is not saved as .txt but as some other unique identifier (for example .prt). I know that's possible with matlab, but I don't know how to get that to work with R.
I can't find any package to do that, and when I try to specify the extension in the file name it give me an error and doesn't save.
Any idea would be greatly welcome! Thank you.
Unless you are using some specialized package, a lot of standard R functions for writing data to files have a file= parameter (or similar) to let you specify whatever the filename (and extension) you want. For example:
dummy.data <- matrix(rnorm(25),ncol=5)
### in reality you could just write file="dummyfile.prt" as one string
### but for demonstration purposes, you can use paste0() or paste(,sep='')
### to create a new file name using some variable prefix and your extension
### ".prt"
### sep='\t' makes the output tab-delimited
write.table(dummy.data,file=paste0("dummyfile",".prt"),sep='\t')
Related
I am using openxlsx in order to write the outputs of my data.
I have used the following code to read my data using readxl.
df1=read_excel("C:/my_data.xlsx",skip=2);
Now I want to write the output and keep the original Excel file using any possible package. I have used the following codes, but it does not keep the original Excel file. Can we do it it in R packages?
write.xlsx(df1, 'C:/mydata.xlsx',skip=2)
Given your code, you should nhave two different data files in your working directory:
"my_data.xlsx" (the one that you loaded), and "mydata.xlsx" (the one that you created through R). R shouldn't overwrite your files if you give them different names.
If there's only one file, are you sure you didn't use the same name for both files? If so, then everything should work fine if you give the files different names (e.g. "my_file1.xlsx" and "my_file2.xlsx")!
Also, in general, it's a good idea to give data files an informative name so that you don't accidentally delete/overwrite files that you need. For example, if the original excel data is you raw data, consider naming it "data_raw.xlsx", and make sure that you only read it, and whenever you make some changes to it, save it under a different name (e.g. "data_processed1.xlsx").
You can also save data files in the native R format .rds using the save_rds() function, this is especially helpful if you want to keep special attributes of variables such as factors, etc...
Hope this helps!
Writing a fresh .Rda file to save a data.frame is easy:
df <- data.frame(a=c(1,2,3,4), b=c(5,6,7,8))
save(df,file="data.Rda")
But is it possible to write more data afterwards, there is no append=TRUE option using save.
Similarly, writing new lines to a text file is easy using:
write.table(df, file = 'data.txt', append=T)
However for large data.frames, the resulting file is much larger.
If you use Microsoft R, you might want to check RevoScaler package, rxImport function in particular. It allows you to store compressed data.frame in file, it also allows you to append new lines to existing file without loading it into environment.
Hope this helps. Link on function documentation below.
https://learn.microsoft.com/en-us/machine-learning-server/r-reference/revoscaler/rximport
I got a question about reading a file into data frame using R.
I don't understand "getwd" and "setwd", do we must do these before reading the files?
and also i need to print some of the columns in the data frame, and only need to print 1 to 30,how to do this?
Kinds regards
getwd tells you what your current working directory is. setwd is used to change your working directory to a specified path. See the relevant documentation here or by typing ? getwd or ? setwd in your R console.
Using these allows you to shorten what you type into, e.g., read.csv by just specifying a filename without specifying its full path, like:
setwd('C:/Users/Me/Documents')
read.csv('myfile.csv')
instead of:
read.csv('C:/Users/Me/Documents/myfile.csv')
I am looking for an easy way to get objects into MS Excel.
(I am using the preinstalled "Puromycin"-dataset for the examples)
I would like to place the contents of these objects to a single excel file:
Puromycin
summary(Puromycin$rate)
summary(Purymycin$conc)
table(Puromycin$state)
lm( conc ~ rate , data=Puromycin)
By "contents" i mean what is shown in the console when i press enter. I dont know what to call it.
I tried to do this:
sink("datafilewhichexcelhopefullyunderstands.csv")
Puromycin
summary(Puromycin$rate)
summary(Purymycin$conc)
table(Puromycin$state)
lm( conc ~ rate , data=Puromycin)
sink()
This gives med a file with the CSV-extension, however when i open the file in notepad,
there is comma-separation. That means that i cant get Excel to open it properly. By properly
i mean that each number is in its own cell.
Others have suggested this for a similar problem
https://stackoverflow.com/a/13007555/1831980
But as a novice i feel that the solution is too complex, and I am hoping for a simpler method.
What I am doing now is this:
write.table(Puromycin, file="clipboard" , sep=";" , row.names=FALSE )
write.table(summary(Purymycin$conc), file="clipboard" , sep=";" , row.names=FALSE )
... etc...
But this requires i lot of copy-ing and pasting, which I hope to eliminate.
Any help would appreciated.
write.table and its friends are intended to write out columns of data separated by whatever separator is specified. Your clipboard contains several data types because you are using summary which always gives a unique output.
For writing the data values out, you can use write.csv on a data frame and then open with Excel. For example, Puromycin is already a data frame (which you can see with str(Puromycin)) so you can just write it out directly:
write.csv(file = "some file.csv", x = Puromycin)
Which will go into the current working directory (which can be determined with getwd()).
To write out/save the results of the regression model is a bit more of a challenge. You could definitely use sink as you did, but specify an extension of .txt on your file so a text editor can open it. There are fancier methods (sweave, knitr) which you might want to look into in the long run, as they can write really nice reports automatically.
In the meantime, get to know str(any R object) as it will be your friend. You can see all the objects in your workspace with ls().
This will only be helpful if you are prepared to use Excel's Data/Text to Columns functions:
capture.output( sapply( c(Puromycin,
summary(Puromycin$rate),
summary(Puromycin$conc),
table(Puromycin$state),
lm( conc ~ rate , data=Puromycin) ), FUN=print), file="datafilewhichexcelhopefullyunderstands.csv", append=TRUE)
The problem being that Excel will not read the whitespace as a cell separator unless you specifically tell it to. You can (and I have often done so) use the fixed filed input features offered by the Text-to-Columns dialog interface.
Your simplest option may be to use the RExcel tool, it transfers information between R and Excel. However it is not free software.
The XLConnect package is another option, it can be used to write information directly to an Excel file.
The tricky part is the lm call. lm does not return a simple vector, matrix, or data frame (all of which are easy to convert to csv or send directly) and there is not a clear way to convert the various parts of a list to cells in a spreadsheet. What would be better is to use extractor functions to pull the important parts from the return of lm or the summary of the lm object and send those to Excel using the other tools.
If you can tell us more about why you want the numbers in Excel and what you plan to do with them after, then we may be able to offer better help (you may be able to completely skip excel).
If the main goal is to share output with others then you should really look at the knitr package (or other related packages). This will not create Excel files, but can be used (along with the pandoc program and possibly other tools) to create a report file in a format easy to share with others not familiar with R. You could put everything into a .pdf file or a .docx file (the latter read by MS Word and would have tables wich can be edited using Word). There is not a simple way to get edits back into R, but with the track changes you can easily see what changes have been made and hand edit your R script/template accordingly.
I am EXTREMELY new to R, and programming in general, so thank you for your patience.
I am trying to write a script which reads values from a .txt file and after some manipulation plots the results. I have two questions which are somewhat coupled.
First, is there a function which asks the user to identify the location of a file? i.e. User runs script. Script opens up file navigation prompt and requests user to navigate to and select relevant file.
Currently, I have to manually identify the file and location in R. e.g.
spectra.raw <- read.table("C:\Users\...\file1.txt", row.names=NULL, header = TRUE)
I'd rather have the user identify the file location each time the script is run. This will be used by non-tech people, and I don't trust them to copy/paste file locations into R.
The second question I've been struggling with is, is it possible to create a variable name based off the file selected? For example, if the user selects "file1.txt" I'd like R to assign the output of read.table() to a variable named "file1.raw" much like the above "spectra.raw"
If it helps, all the file names will have the exact same number of characters, so if it's possible to select the last say 5 characters from the file location, that would work.
Thank you very much, and please excuse my ignorance.
See file.choose. Though I believe it behaves slightly differently on different platforms, so beware of that.
See assign, i.e. assign("fileName",value). You'll want to parse the file path that file.choose spits back using string manipulation functions like substr or strsplit.
Try
file.choose
I think it can do what you want.
For example,
myfile <- file.choose()
Enter file name: adataset.Rdata
load(myfile)
myfile contains the name of the file so you don't have to do anything special.