How do I export a data frame from R (the file is in Global Environment) to some folder in desktop? I have created some data frames in R and need to export to the linux operating system. That's why I want to export the data frame to desktop/documents and later export to the Linux.
The Save function can do that, just specify the path you want to export the data. Change your directory in Rstudio to that folder in the desktop or else save it somewhere and do a cp linux command.
Save Function Information
Save Data Frame (Stack Overflow)
saving a data file in R
To write a data frame to a text file, the command is write.table. I'll let you read the help (?write.table) to see all the options, but a sample usage is
write.table(x = mtcars, file = "C:/exported_mtcars.txt")
This will write the data frame called mtcars to a file called exported_mtcars.txt on my C drive. The default is to use spaces to separate columns. If you want tab-separations, specify sep = "\t".
You may want to simply set your working directory to the folder you've created (setwd("C:/Users/...your filepath.../Desktop/your_folder")). Then you can just specify, e.g., file = "file1.txt" for the file names in write.table.
As far as writing multiple data frames to multiple files, I strongly recommend working with lists of data frames. I'll refer you to my answer here on the subject. See especially the section I didn't put my data in a list :( I will next time, but what can I do now?. You can then pretty easily use a for loop to save all your data frames to files using write.table.
You have to specify here the route where you want to export a complete image of your current working environment:
save.image("~/User/RstudioFiles/dataset.RData")
Hope it works!
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!
I define a DataFrame named data and want to write it into .csv file. I used writetable("result_data.csv", data) but it doesn't work.
This is the dataframe
error details
To write a data frame to a disk you should use the CSV.jl package like this (also make sure that you have write right to the directory you want to save the file on Juliabox):
using CSV
CSV.write("result_data.csv", data)
If this fails then please report back in the comment I will investigate it further.
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 would like to clarify my understanding here on both converting a file into CSV and also reading it. Let's use a dataset from R for instance, titled longley.
To set up a data frame, I can just use the write.table command as follows, right?
d1<-longley
write.table(d1, file="", sep="1,16", row.names=TRUE, col.names=TRUE)
Has this already become a data frame or am I missing something here?
Now let's say if I want to read this CSV file. Then would my code be something like:
read.table(<dframe1>, header=FALSE, sep="", quote="\"")
It seems like before that I have to use a function called setwd(). I'm not really sure what it does or how it helps. Can someone help me here?
longley and, therefore, d1 are already data frames (type class(d1) in the console). A data frame is a fundamental data structure in R. Writing a data frame to a file saves the data in the data frame. In this case, you're trying to save the data in the data frame in CSV format, which you would do like this:
write.csv(d1, "myFileName.csv")
write.csv is a wrapper for write.table that takes care of the settings needed for saving in CSV format. You could also do:
write.table(d1, "myFileName.csv", sep=",")
sep="," tells R to write the file with values separated by a comma.
Then, to read the file into an R session you can do this:
df = read.csv("myFileName.csv", header=TRUE, stringsAsFactors=FALSE)
This creates a new object called df, which is the data frame created from the data in myFileName.csv. Once again, read.csv is a wrapper for read.table that takes care of the settings for reading a CSV file.
setwd is how you change the working directory--that is, the default directory where R writes to and reads from. But you can also keep the current working directory unchanged and just give write.csv or read.csv (or any other function that writes or reads R objects) the full path to wherever you want to read from or write to. For example:
write.csv(d1, "/path/for/saving/file/myFileName.csv")
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')