I have a question which is exactly similar to this question.
As part of my work, I have to copy output from the R Studio Console to an excel worksheet in order to make excel graphs. However, the R Studio Console uses formatted text, which excel doesn't read so well. To compensate, I'm always copying from the R Studio Console, pasting into notepad, then copying into Excel. That way, when I paste a table, I can tell excel that it's actually fixed width delimited data, and not just a clump of text.
How can I copy output from the R Studio console so that it goes into the clipboard as unformatted text so that I can paste it directly into Excel and thus organize the numbers into different cells? This would be very helpful as I dislike having to copy/paste tables into notepad then excel to make graphs.
It works with an easy trick.
First, you have to visualize your data in the Viewer pane of Rstudio (you can use the function View()), then you should start selecting from the last value to the first, it is from bottom to top (see image). Note that the first cell should be selected completely. Finally, right click on the selection, copy, and then paste it in Excel as you want, with or without format.
Good luck!
UPDATE:
based on this Post, other alternative is making a new function to copy your data.frame to Excel through the clipboard:
write.excel <- function(x,row.names=FALSE,col.names=TRUE,...) {
write.table(x,"clipboard",sep="\t",row.names=row.names,col.names=col.names,...)
}
write.excel(my.df)
and finally Ctr+V in Excel :)
This is by far the easiest way I have found so far:
clipr::write_clip(my_df)
source here
I usually source the following function:
cb <- function(df, sep="\t", dec=",", max.size=(200*1000)){
# Copy a data.frame to clipboard
write.table(df, paste0("clipboard-", formatC(max.size, format="f", digits=0)), sep=sep, row.names=FALSE, dec=dec)
}
A few notes:
Max.size allows you to specify how big the clipboard can become (in kilobytes) before it cancels, it's set to ~200MB right now.
It works perfectly for copying an R dataframe from an R studio session to Excel (with my EU locale). You might have to adjust the separator / decimal symbols to make it work with US versions.
How to use:
df <- mtcars
cb(df)
# Paste in excel as 'values'
From my experience there is no convenient way, I use two methods:
For small data frames, use RStudio's View(data.frame) function, if you copy only data without headers it works fine, but if you want to copy with headers then you have to paste it into notepad first to add at least one character to the top left empty cell.
For large data frames, use write.csv or write.xls (from package WriteXLS)
Related
I write data frames to csv files using write.csv(). When this is done, the output when viewed in a plain text editor, in particular vi or notepad++, shows no spacing between the column content and the commas, resulting in it being relatively hard to read. For example, the columns are not lined up down the page.
I have negative interest in using excel to view the csv files. I am definitely not looking for a suggestion for a csv viewer. Nor do I want instructions on how to modify the plain text file afterward. Padding needs to be spaces not tabs.
I am interested in how to get R to line up the columns in the plain text csv file so that they are easier to read using a non specialized plain text editor.
I could (and might) write my own routine that converts everything to some fixed width string format and print that. But, I would prefer to find that this is an option within write.csv() or similar common output library call.
[I just this moment found out about printf in R, and that might be the best answer to this conundrum].
I have a relatively simple issue when writing out in R with fwrite from the data.table package I am getting a character vector interpreted as scientific notation by Excel. You can run the following code to create the data issue:
#create example
samp = data.table(id = c("7E39", "7G32","5D99999"))
fwrite(samp,"test.csv",row.names = F)
When you read this back into R you get values back no problem if you have scinote disable. My less code capable colleagues work with the csv directly in excel and they see this:
They can attempt to change the variable to text but excel then interprets all the zeros. I want them to see the original "7E39" from the data table created. Any ideas how to avoid this issue?
PS: I'm working with millions of rows so write.csv is not really an option
EDIT:
One workaround I've found is to just create a mock variable with quotes:
samp = data.table(id = c("7E39", "7G32","5D99999"))[,id2:=shQuote(id)]
I prefer a tidyr solution (pun intended), as I hate unnecessary columns
EDIT2:
Following R2Evan's solution I adapted it to data table with the following (factoring another numerical column, to see if any changes occured):
#create example
samp = data.table(id = c("7E39", "7G32","5D99999"))[,second_var:=c(1,2,3)]
fwrite(samp[,id:=sprintf("=%s", shQuote(id))],
"foo.csv", row.names=FALSE)
It's a kludge, and dang-it for Excel to force this (I've dealt with it before).
write.csv(data.frame(id=sprintf("=%s", shQuote(c("7E39", "7G32","5D99999")))),
"foo.csv", row.names=FALSE)
This is forcing Excel to consider that column a formula, and interpret it as such. You'll see that in Excel, it is a literal formula that assigns a static string.
This is obviously not portable and prone to all sorts of problems, but that is Excel's way in this regard.
(BTW: I used write.csv here, but frankly it doesn't matter which function you use, as long as it passes the string through.)
Another option, but one that your consumers will need to do, not you.
If you export the file "as is", meaning the cell content is just "7E39", then an auto-import within Excel will always try to be smart about that cell's content. However, you can manually import the data.
Using Excel 2016 (32bit, on win10_64bit, if it matters):
Open Excel (first), have an (optionally empty) worksheet already open
On the ribbon: Data > Get External Data > From Text
Navigate to the appropriate file (CSV)
Select "Delimited" (file type), click Next, select "Comma" (and optionally deselect any others that may default to selected), Next
Click on the specific column(s) and set the "Default data format" to "Text" (this will need to be done for any/all columns where this is a problem). Multiple columns can be Shift-selected (for a range of columns), but not Ctrl-selected. Finish.
Choose the top-left cell to import/paste the data (or a new worksheet)
Select Properties..., and deselect "Save query definition". Without this step, the data is considered a query into an external data source, which may not be a problem but makes some things a little annoying. (For example, try to highlight all data and delete it ... Excel really wants to make sure you know what you're doing there.)
This method provides a portable solution. It "punishes" the Excel users, but anybody/anything else will still be able to consume the files directly without change. The biggest disadvantage with this method is that you won't know if somebody loads it incorrectly unless/until they get odd results when the try to use the data and some fields are silently converted.
I am wondering is it possible to read an excel file that is currently open, and capture things you manually test into R?
I have an excel file opened (in Windows). In my excel, I have connected to a SSAS cube. And I do some manipulations using PivotTable Fields (like changing columns, rows, and filters) to understand the data. I would like to import some of the results I see in excel into R to create a report. (I mean without manually copy/paste the results into R or saving excel sheets to read them later). Is this a possible thing to do in R?
UPDATE
I was able to find an answer. Thanks to awesome package created by Andri Signorell.
library(DescTools)
fxls<-GetCurrXL()
tttt<-XLGetRange(header=TRUE)
I was able to find an answer. Thanks to awesome package created by Andri Signorell.
library(DescTools)
fxls<-GetCurrXL()
tttt<-XLGetRange(header=TRUE)
Copy the values you are interested in (in a single spread sheet at a time) to clipboard.
Then
dat = read.table('clipboard', header = TRUE, sep = "\t")
You can save the final excel spreadsheet as a csv file (comma separated).
Then use read.csv("filename") in R and go from there. Alternatively, you can use read.table("filename",sep=",") which is the more general version of read.csv(). For tab separated files, use sep="\t" and so forth.
I will assume this blog post will be useful: http://www.r-bloggers.com/a-million-ways-to-connect-r-and-excel/
In the R console, you can type
?read.table
for more information on the arguments and uses of this function. You can just repeat the same call in R after Excel sheet changes have been saved.
So I have a bunch of .csv files that were output by a simulation. I'm writing an R script to run through them and make a histogram of a column in each .csv file. However, the .csv is written in such a way that R does not like it. When I was testing it, I had been originally opening the files in Excel and apparently this changed the format to one R liked. Then when I went back to run the script on the entire folder I discovered that R doesn't like the format.
I was reading the data in as:
x <- read.csv("synch-imit-characteristics-2-tags-2-size-200-cost-0.1run-2-.csv", strip.white=TRUE)
Error in read.table(test, strip.white = TRUE, header = TRUE) :
more columns than column names
Investigating I found that the original .csv file, which R does not like, looks different than after the test one I opened with excel. I copied and pasted the first bit below after opening it in notepad:
cost,0.1
mean-loyalty, mean-hospitality
0.9885449527316088, 0.33240076252915735
weight,1 of p1, 2 of p1,
However, in notepad, there is no apparent formatting. In fact, between rows there is no space at all, ie it is cost,0.1mean-loyalty,mean-hospitality0.988544, etc. So it is weird to me as well that when I cope and paste it from notepad it gets the desired formatting as above. Anyway, moving on, after I had opened it in excel it got transferred to this"
cost,0.1,,,,,,,,
mean-loyalty, mean-hospitality,,,,,,,,
0.989771257,0.335847092,,,,,,,,
weight,1 of p1, etc...
So it seems like the data originally has no separation between rows (but I don't know how excel figures it out, or copying and pasting it) but R doesn't pick up on this. Instead, it views it all as one row (and since I have 40,000+ rows, it doesn't have that many columns). I don't want to have to open and save every file in excel. Is there a way to get R to read the data as desired?
Since when I copy and paste it from notepad it had new lines for the rows, it seems like I just need R to read it knowing that commas separate columns on the same row and a return separates rows. I tried messing around with all the sep="" commands I could find. But I can't figure it out.
To first solve the Notepad issue:
You must have CR (carriage return, \r) characters between the lines (and no LF, \n characters, causing Notepad to see it as one line).
Some programs accept this as well as a new line character, some don't.
You can for example use Notepad++ to replace all '\r' with '\n' or '\r\n', using Replace wih the "Extended" option. First select View > Show Symbol > Show all characters, so see what you are doing.
Finally, to get back to R:
(As it was pointed out, R can actually handle CR as a newline)
read.csv assumes that you have non-empty header names in the first row, but instead you have:
cost,0.1
while later in the data you have a row with more than just two columns:
weight,1 of p1, 2 of p1,
This means that not all columns have a header name (and I wonder if 0.1 was supposed to be a header name anyway).
The two solutions can be:
add a header including all columns, or
as it was pointed out in a comment use header=F.
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.