Tablizer

Convert YAML to R DataFrame Online

Paste a YAML 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 YAML is

YAML uses indentation instead of brackets. It is a superset of JSON, supports comments, and is meant to be edited by hand.

Kubernetes manifests, CI pipelines, Ansible playbooks and most modern config files.

What R DataFrame is

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

Statistics and R notebooks.

What changes when you convert YAML to R DataFrame

A YAML list of maps reads as rows and columns directly. Anchors and aliases are resolved before the table is built, so a repeated block arrives expanded rather than as a reference.

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 YAML to R DataFrame

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

YAML 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.

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.

YAML 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 YAML to R DataFrame?

Paste your YAML 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.

Why did my YAML value change meaning?

YAML reads several bare words as booleans. In the 1.1 spec that includes yes, no, on and off, which is why a country column containing NO for Norway can arrive as false. Quote values you want kept as text.

What happens to nested values?

R data frame has no nested cell, so a list or object inside a YAML 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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