I've been researching into this question, which I assume should be easy to fix, but am not having any luck. I have an excel file where each cell is some text of variable length. I'm wanting to read this into R so I can eventually do some text classification, but am failing. I get errors when using read.table and am struggling with all other alternatives. I've never worked with text data before so perhaps this is my issue. Having problems finding good examples of importing text data into R when it isn't in a corpus format.
There are special packages for reading data from the excel format. I mostly use readxl when I need to do this, but I know that there are several (a lot of them are described in this tutorial by datacamp, in the section Importing Excel files into R).
Another possibility (assuming you are using windows) is to copy the cells to the clipboard and use
read.table("clipboard")
for macOS and Linux there are similar commands, but I don't know them by heart.
Related
I have a 174603 rows and 178 column dataframe, which I'm importing to Excel using openxlsx::saveWorkbook, (Using this package to obtain the aforementioned format of cells, with colors, header styles and so on). But the process is extremely slow, (depending on the amount of memory used by the machine it can take from 7 to 17 minutes!!) and I need a way to reduce this significantly (Doesn't need to be seconds, but anything bellow 5 min would be OK)
I've already searched other questions but they all seem to focus either in exporting to R (I have no problem with this) or writing non-formatted files to R (using write.csv and other options of the like)
Apparently I can't use xlsx package because of the settings on my computer (industrial computer, Check comments on This question)
Any suggestions regarding packages or other functionalities inside this package to make this run faster would be highly appreciated.
This question has some time ,but I had the same problem as you and came up with a solution worth mentioning.
There is package called writexl that has implemented a way to export a data frame to Excel using the C library libxlsxwriter. You can export to excel using the next code:
library(writexl)
writexl::write_xlsx(df, "Excel.xlsx",format_headers = TRUE)
The parameter format_headers only apply centered and bold titles, but I had edited the C code of the its source in github writexl library made by ropensci.
You can download it or clone it. Inside src folder you can edit write_xlsx.c file.
For example in the part that he is inserting the header format
//how to format headers (bold + center)
lxw_format * title = workbook_add_format(workbook);
format_set_bold(title);
format_set_align(title, LXW_ALIGN_CENTER);
you can add this lines to add background color to the header
format_set_pattern (title, LXW_PATTERN_SOLID);
format_set_bg_color(title, 0x8DC4E4);
There are lots of formating you can do searching in the libxlsxwriter library
When you have finished editing that file and given you have the source code in a folder called writexl, you can build and install the edited package by
shell("R CMD build writexl")
install.packages("writexl_1.2.tar.gz", repos = NULL)
Exporting again using the first chunk of code will generate the Excel with formats and faster than any other library I know about.
Hope this helps.
Have you tried ;
write.table(GroupsAlldata, file = 'Groupsalldata.txt')
in order to obtain it in txt format.
Then on Excel, you can simply transfer you can 'text to column' to put your data into a table
good luck
I have been practicing with tabulizer package in R and have following problem. Unfortunately I can't offer reproducible example, as pdf is firms property, but I will describe problem in detail.
I'm trying to read PDF that has start and end date in upperright corner. When I open PDF they look normal
Start: 01-Mar-2018
End: 31-Mar-2018
Now the fun part. When I highlight them and use Ctrl+C to copy them here is result when pasted to R.
:tttt: 11-rrr-8118
tt:: 11-rrr-8118
This is exactly same kind of nonsense that extract_text(path, pages=1) will give. A lot of t::ttttt:ttt... My question is that is there some security in this PDF or do I just need to figure out correct encoding or because this PDF is automatically created from system, there is some weird notation to everything?
I figured it out. This PDF is mainly created by metadata (didn't know) and great tool in R for accessing metadata in PDFs is pdftools.
library(pdftools)
pdf_info(path.pdf)
and you can wrangle out all the important metadata bits.
I got the output file from a spectrometer which is supposed to be a series of decimals numbers. The file looks like this:
™pQH1JHxþFH$ÏFH÷~EHa×BHäBHßdBH.#H²Ï=HL=HŒÚ<Hê‰:HP:Hoõ9H¢Ž6Hº7H¨Y5H ?1H½¶.Hø²0HøŽ2H8æ.H.î,HŒt/H&1H͸0Hí.Hvî,H$ª+HµX+HCý*H·W+H!º+HP+HfØ(Hû'H†Ù'H|U(HQ`)Hn*H
})H'Hó%HÂ%H¶¨&H&H|•&H\
I have been reading a lot without getting to the solution. My silly question is: is that a ENVI or ASCII file? Or? How can I see the numbers I need do to use? I tried some online converters without being successful.
The starting point would be to get these numbers to develop a R code to make graphs. Thanks a lot for your time.
This looks like you opened the binary file of the mass spectrometer. Almost all vendors keep their format a secret. The only way to do this is to export it to an open format. Most vendors supply some kind of data analysis software and there are often export functions present. Most general open data formats are mzXML and mzML.
For converting have a look at the msconvert program from ProteoWizard.
If you have converted the data one of the packages in R where you can start with is XCMS.
If I load data(mtcars) it comes with a very neat codebook that I can call using ?mtcars.
I'm interested to document my data in the same way and, furthermore, save that neat codebook as a pdf.
Is it possible to save the 'content' of ?mtcars and how is it created?
Thanks, Eric
P.S. I did read this thread.
update 2012-05-14 00:39:59 PDT
I am looking for a solution using only R; unfortunately I cannot rely on other software (e.g. Tex)
update 2012-05-14 09:49:05 PDT
Thank you very much everyone for the many answers.
Reading these answers I realized that I should have made my priorities much clearer. Therefore, here is a list of my priorities in regard to this question.
R, I am looking for a solution that is based exclusively on R.
Reproducibility, that the codebook can be part of a automated script.
Readability, the text should be easy to read.
Searchability, a file that can be open with any standard software and searched (this is why I thought pdf would be a good solution, but this is overruled by 1 through 3).
I am currently labeling my variables using label() from the Hmisc package and might end up writing a .txt codebook using Label() from the same package.
(I'm not completely sure what you're after, but):
Like other package documentation, the file for mtcars is an .Rd file. You can convert it into other formats (ASCII) than pdf, but the usual way of producing a pdf does use pdflatex.
However, most information in such an .Rd file is written more or less by hand (unless you use yet another R package like roxygen/roxygen2 help you to generate parts of it automatically.
For user-data, usually Noweb is much more convenient.
.Rnw -Sweave-> -> .tex -pdflatex-> pdf is certainly the most usual way with such files.
However, you can use it e.g. with Openoffice (if that is installed) or use it with plain ASCII files instead of TeX.
Have a look at package knitr which may be easier with pure-ASCII files. (I'm not an expert, just switching over from Sweave)
If html is an option, both Sweave and knitr can work with that.
I don't know how to get the pdf of individual data sets but you can build the pdf of the entire datasets package from the LaTeX version using:
path <- find.package('datasets')
system(paste(shQuote(file.path(R.home("bin"), "R")),"CMD",
"Rd2pdf",shQuote(path)))
I'm not sure on this but it only makes sense you'd have to have some sort of LaTeX program like MikTex. Also I'm not sure how this will work on different OS as mine is windows and this works for me.
PS this is only a partial answer to your question as you want to do this for your data, but if nothing else it may get the ball rolling.
The help page that is displayed when entering ?mtcars is generated from an .Rd file, which is a LaTeX-like file that is used for all of R's help pages. Although .Rd files are LaTeX-like, you don't actually need to know LaTeX to read or write them. The actual mtcars.Rd file is available here: http://commondatastorage.googleapis.com/jthetzel-public/mtcars.Rd , which can be viewed with any text editor.
.Rd files included in the ./man directory of a package are converted to .html files when installing the package. They are converted by functions in the "tools" package.. If you would like functionality like ?mtcars for your datasets, you would need to create a package for them. That might sound complicated if you have never created a package before, but it is easy enough to learn and will make you a better R programmer. There are a number of examples of dataset-only packages on CRAN, for example msProstate: http://cran.r-project.org/web/packages/msProstate/index.html . Consider downloading the package source to see how it is organized.
For more information on creating your own packages, writing .Rd files, and building packages:
http://cran.r-project.org/doc/manuals/R-exts.html, especially "1.1.5 Data in packages".
Edit
And if you want to convert the .Rd file in your package to a .pdf, you can do so when building your package, but you will need a LaTeX compiler. If you are on Windows, see here: http://cran.r-project.org/bin/windows/Rtools/ .
You can't create a PDF with just R; you need to use other software that creates PDFs.
You could use a combination of utils::promptData, tools::Rd2HTML, and a simple custom function to open the created HTML file in the users' browser.
It would probably be easier to just make a package containing your data sets. Look at the "datasets" package for an example.
It looks like that if you want to generate a pdf, an external tool like LaTeX is always needed. I would recommend using a simple ASCII text format to generate such a file. In principle the .Rd files are also ASCII text, but I do not find them particularly readable.
Instead, I would recommend using a plain text ASCII format such as Markdown (which is e.g. used on StackOverflow) to write the text file. Such a file is already much more readable than an .Rd formatted file, and as a bonus it can quite easily be processed into a PDF should you choose to do so later on. The knitr package I think is capable of generating PDF files from Markdown sources. In addition, knitr allows you to mix in R code in the Markdown text. This code can be evaluated and the results (even figures) added to the resulting PDF.
In practice you can use sprintf to generate character vectors that you can pipe to a file in order to dynamically generate the markdown text. Just write the template one time, and mark the places for the text you want to add later like this:
base_text = "
First header
============
This document was generated on %s, by %s.
"
text_forfile = sprintf(text, some_date, some_name)
Just dump the text in text_forfile to a .md file and your done, no external tools needed. See this post on SO for how dump text to a file.
I've used RODBC for some time to import Excel spreadsheets with mostly good results. However I have had no luck writing to an Excel spreadsheet. Also are there favorable differences using the xlsx format with Excel2007?
I've used the technique described here: Export Data Frames To Multi-worksheet Excel File
The R Data Import/Export manual should be considered the best source of advice for these questions.
For reading you can indeed use the RODBC package. An easier solutoion may be read.xls() from the gdata
For writing you can use one of the wrapper packages such as WriteXLS which wraps around Perl libraries that know how to write in the proprietary and not formally documented xls format.
In general, xlsx will not be a solution as this format is newer, once again proprietary and not documented. For that reason there are even fewer tools coping with this.
XLConnect works well. It is cross-platform. It can read and write xls and xlsx files. See this previous answer
This question is 3 years old, but I'll throw this in: if you want to write to the spreadsheet, remember to add readOnly=FALSE as an argument to odbcConnectExcel and odbcConnectExcel2007.
There is a package that may help with dealing with excel 2007, but I haven't tried it.
http://www.omegahat.org/RExcelXML/