Convert Plain Text to R DataFrame Online

Paste a Plain Text table below, edit it if you need to, and get R DataFrame back. The conversion runs in your browser, so nothing is uploaded, there is no size limit and there is no signup.

From

From a page

The only part of this site that uses a server. The address is sent to it so the page can be fetched, because a browser is not allowed to fetch someone else's page itself. Your own files are never involved.

Nothing here is uploaded. The parsing happens on this page.

Edit

Paste or upload something above and it will appear here.

ToDataMarkupDocumentsCodeSchemasImages

Header rowDetect numbers

The output will appear here once there is a table to convert.

What Plain Text is

Plain text here means columns lined up with spaces, the way a command line tool prints a table.

Terminal output, log files, fixed-width exports from older systems.

What R DataFrame is

R code that builds a data.frame from character vectors.

Statistics and R notebooks.

What changes when you convert Plain Text to R DataFrame

Two shapes are handled. If the same character positions are blank on every line, those gutters are treated as column boundaries, so values containing single spaces stay intact. Otherwise the lines are split on runs of whitespace.

stringsAsFactors is set to FALSE explicitly. It has defaulted to FALSE since R 4.0, but being explicit means the snippet behaves the same on older installs.

What carries over from Plain Text to R DataFrame

R data frame can express everything plain text holds about a table, so this conversion is about shape rather than loss.

R data frame wants a type for each column, and plain text does not record one, so each column is typed from what its values look like. A column of digits that should stay text - a zip code, a phone number, a leading-zero id - is the usual thing to check afterwards.

R data frame marks its header cells differently from its data cells, so the first row is written with that marker.

The identifier 007 comes out of the R DataFrame as 007. Reading it as a number would have made it 7, and an id that changes value is worse than one that stays text.

The role "Analyst, data" survives with its comma, in one cell rather than split across two. That is the first thing to check in any converted table, and the usual place a R DataFrame file goes wrong.

The quotes around Jonah "Jo" Pryce are escaped with a backslash in the R DataFrame.

A worked example

Three rows of staff data, with an identifier that has a leading zero, a value containing a comma, a value containing quotes and one blank cell. Those are the four places formats disagree, so they are the four places to look.

Plain Text in

id   name              role           started     hours
007  Halima Yusuf      Analyst, data  2024-03-15  38.5
012  Jonah "Jo" Pryce  Engineer       2025-11-02
104  Wei Chen          Manager        2023-06-30  40

R DataFrame out

staff <- data.frame(
  id = c("007", "012", "104"),
  name = c("Halima Yusuf", "Jonah \"Jo\" Pryce", "Wei Chen"),
  role = c("Analyst, data", "Engineer", "Manager"),
  started = c("2024-03-15", "2025-11-02", "2023-06-30"),
  hours = c("38.5", "", "40")
  , stringsAsFactors = FALSE
)

Questions

How do I convert Plain Text to R DataFrame?

Paste your Plain Text into the box above or drop the file onto it. Check the table in the grid, then copy or download the R DataFrame from the output panel. It takes one step and the data never leaves your browser.

Is there a limit on file size?

No. The work happens on your own machine, so the limit is your machine's memory rather than an upload cap. A file with tens of thousands of rows converts in a second or two.

Is my data uploaded anywhere?

No. The parsing and generating are done by JavaScript running on this page. You can watch the network tab while you convert and see that nothing is sent.