Tablizer

Convert JSON Lines to R DataFrame Online

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

What JSON Lines is

JSON Lines is one complete JSON object per line, with no enclosing array and no commas between records. The file is not valid JSON as a whole, and that is the point.

Log pipelines, machine learning datasets and anything that appends records or reads them in a stream.

What R DataFrame is

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

Statistics and R notebooks.

What changes when you convert JSON Lines to R DataFrame

Each line is parsed on its own, so a corrupt record does not take the file with it. Keys are unioned across lines in first-seen order, so a record missing a field leaves that cell empty rather than shifting the columns.

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 JSON Lines to R DataFrame

JSON Lines records 2 things about a table that R data frame has no way to hold.

JSON Lines can hold a value that is itself a list or an object. R data frame has only flat cells, so nested values are flattened into one cell rather than being spread across columns.

R data frame marks header cells differently from data cells, so the keys are lifted out and written once as a marked header row rather than repeated on every row.

JSON Lines 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.

Both formats record types, so numbers, booleans and nulls survive as themselves rather than as text.

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.

JSON Lines in
{"id":"007","name":"Halima Yusuf","role":"Analyst, data","started":"2024-03-15","hours":"38.5"}
{"id":"012","name":"Jonah \"Jo\" Pryce","role":"Engineer","started":"2025-11-02","hours":""}
{"id":"104","name":"Wei Chen","role":"Manager","started":"2023-06-30","hours":"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 JSON Lines to R DataFrame?

Paste your JSON Lines 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.

What is the difference between JSON and JSON Lines?

JSON wraps records in an array, so a reader must load the whole document before it can use any of it, and appending means rewriting the file. JSON Lines has no wrapper, so records can be streamed and appended one at a time. Use JSON for a payload, JSON Lines for a log.

What happens to nested values?

R data frame has no nested cell, so a list or object inside a JSON Lines value is flattened into a single cell rather than expanded into extra columns. Split it before converting if the parts need to be separate.

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.

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