Things to check before integrating
Before you integrate
Select and flatten the required record fields before sending nested JSON.
Before you integrate
Original data types are not restored automatically; validate identifiers and convert vectors before analysis.
Code examples
These examples send the sample as multipart/form-data and save the returned bytes unchanged. Set TABLECONVERT_API_KEY in your environment.
JSON to R data.frame code API · cURL
curl --fail-with-body --max-time 40 \
'https://api.tableconvert.com/v2/convert/json-to-rdataframe' \
--header "Authorization: Bearer $TABLECONVERT_API_KEY" \
--form-string 'data=[
{
"category": "Supplies",
"amount": "125",
"region": "North"
},
{
"category": "Equipment",
"amount": "480",
"region": "South"
}
]' \
--output 'json-to-rdataframe.R'Requires cURL. Download the sample input first when this example uploads a file.
JSON to R data.frame code API · Python
import os
from pathlib import Path
import requests
endpoint = "https://api.tableconvert.com/v2/convert/json-to-rdataframe"
headers = {"Authorization": "Bearer " + os.environ["TABLECONVERT_API_KEY"]}
fields = {
"data": (None, "[\n {\n \"category\": \"Supplies\",\n \"amount\": \"125\",\n \"region\": \"North\"\n },\n {\n \"category\": \"Equipment\",\n \"amount\": \"480\",\n \"region\": \"South\"\n }\n]"),
}
response = requests.post(endpoint, headers=headers, files=fields, timeout=40)
response.raise_for_status()
Path("json-to-rdataframe.R").write_bytes(response.content)Requires Python 3 and requests. Install it with pip install requests.
JSON to R data.frame code API · Node.js
import { writeFile } from "node:fs/promises";
const form = new FormData();
form.set("data", "[\n {\n \"category\": \"Supplies\",\n \"amount\": \"125\",\n \"region\": \"North\"\n },\n {\n \"category\": \"Equipment\",\n \"amount\": \"480\",\n \"region\": \"South\"\n }\n]");
const response = await fetch("https://api.tableconvert.com/v2/convert/json-to-rdataframe", {
method: "POST",
headers: { Authorization: "Bearer " + process.env.TABLECONVERT_API_KEY },
body: form,
signal: AbortSignal.timeout(40_000),
});
if (!response.ok) {
throw new Error("HTTP " + response.status + ": " + await response.text());
}
await writeFile("json-to-rdataframe.R", Buffer.from(await response.arrayBuffer()));Requires Node.js 20 or later with built-in fetch, FormData and Blob.
Authentication
Send Authorization: Bearer YOUR_API_KEY. Let the HTTP client set the multipart boundary; do not set Content-Type manually.
Keep production API keys in server-side environment variables.
Request parameters
A nonempty array of flat objects is the clearest record input. Object keys form a union of columns; nested structures are not automatically flattened.
| Parameter | Type | Default | Description |
|---|---|---|---|
data | string | — | Inline JSON table content. Choose one of data, file or url. |
file | binary | — | Upload a json file using multipart/form-data. |
url | string | — | A supported publicly accessible HTTP or HTTPS file URL. |
Send one source: data, file, or url. The examples below use the source mode appropriate for this format.
Output options
Generate R source using data.frame and one c(...) vector per column. Values are emitted as strings and the API does not execute R.
This output format does not expose additional options.
Conversion rules
| Case | Behavior |
|---|---|
| Mapping rule 1 | The union of object keys forms the header, and each flat object supplies one row of text cells. |
| Mapping rule 2 | Columns are transposed into character vectors named from the header. |
| Mapping rule 3 | JSON scalar types pass through text cells before code generation; explicitly cast analytical columns and prepare nested arrays first. |
How the input is read
- For object arrays, columns follow keys in first-seen order; missing keys yield empty cells.
- null becomes the literal text null, while numbers and booleans become text during table normalization.
- A nested object becomes [object Object]; an array inside a field becomes comma-joined text rather than additional rows.
- Prepare explicit flat fields before conversion; the endpoint has no generic flatten parameter.
How the output is written
- Headers become argument names and columns become quoted vectors.
- Convert numeric, factor and date columns explicitly in R when the analysis requires them.
- Validate R identifiers and string quoting; the returned representation is code text regardless of the download extension.
When to use this API
This conversion in practice
Use an application JSON response as the starting dataset for an R analysis or package-test fixture. Select and flatten the required record fields before sending nested JSON.
R data.frame code
Prepare reproducible data.frame construction for a small R analysis fixture.
Responses and errors
| HTTP status | Description |
|---|---|
200 | text/plain; charset=utf-8 |
400 | Invalid input or conversion parameters. |
402 | Insufficient credits for this request. |
403 | Missing or invalid API key. |
413 | The input exceeds the configured request limit. |
415 | Unsupported input media type. |
429 | Rate limit exceeded. |
500 | The conversion could not be completed. |
503 | The renderer is unavailable or the request timed out. |
Check the response before retrying. A new HTTP request is a new conversion and may use credits again.
Limits, billing and versions
Local previews accept up to 200 KB. The current API implementation allows one uploaded file up to 50 MiB, limits each multipart text field to 1 MiB, and gives v2 conversion tasks a 30-second deadline. Deployment limits may be stricter. Read the returned error before retrying; some parser or renderer failures return HTTP 500.
Live calls follow the API credit policy. Failed conversions are refunded; a completed conversion is not undone if the download connection later fails.
View API pricing and creditsUsing API v1?
This page documents v2, which returns the output directly. API v1 wraps the result in a JSON envelope. Check the overview before changing an existing integration.
API overviewReferences and format specifications
Format references explain the underlying syntax. The conversion rules and samples above describe TableConvert’s implementation.