Convert TSV to R DataFrame Online

Paste a TSV 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.

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

Edit

Paste or upload something above and it will appear here.

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Header rowDetect numbers

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

What TSV is

TSV is CSV with tabs instead of commas. Because tabs almost never appear inside a value, quoting is rarely needed and the files are easier to read by eye.

Bioinformatics, log processing, and anyone who has copied a block of cells out of a spreadsheet: the clipboard format is TSV.

What R DataFrame is

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

Statistics and R notebooks.

What changes when you convert TSV to R DataFrame

The tab is unambiguous, so there is no delimiter to guess. This is the most reliable of the delimited formats to read.

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 TSV to R DataFrame

One property of the TSV has no home in R data frame, and it is worth knowing which before you convert.

R data frame wants a type for each column, and TSV 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.

TSV can be read one record at a time. R data frame has to be complete before it means anything, so the whole table is held in memory while it is written and a file that gets cut off part way through is not partly usable - it is unusable.

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.

TSV 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 TSV to R DataFrame?

Paste your TSV 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.