Table to JSON result preview — CSV and table to JSON, JSONL and SQL INSERT converter

CSV to JSON Converter — Convert a Table to JSON Online

Convert CSV, TSV, pipe-delimited or Markdown tables into JSON, JSONL or SQL INSERT statements in your browser.

Paste a table or drop a CSV — get JSON, JSONL or SQL out the other side

or drop a .csv / .tsv file

How to convert a CSV or table to JSON, JSONL or SQL INSERT statements

This table converter turns pasted CSV, TSV, semicolon-separated or pipe-separated data, or a Markdown table, into a JSON array, JSONL or SQL INSERT statements. It detects the delimiter, reads quoted fields and uses the first row as field names unless you untick First row is header. Paste data or open a .csv file, pick an Output, then copy or download the result. The conversion runs in your browser.

Convert CSV to JSON with the first row as keys

Paste the table into Input Table, and with Delimiter on Auto-detect the tool counts tabs, commas, semicolons and pipes in the first line and uses the most frequent one. The input name,age,city followed by the row Alice,34,Berlin becomes a JSON array holding one object with those three keys. JSON (arrays) writes each data row as a plain list without keys and leaves out the header row, and JSONL writes one object per line with no surrounding array. A Markdown table needs Markdown table chosen under Delimiter, because Auto-detect reads it as pipe-separated text. If your table is stuck in a document, convert the PDF to CSV first.

  1. Paste the table into Input Table, or open a .csv or .tsv file.
  2. Leave Delimiter on Auto-detect, or choose it yourself.
  3. Choose JSON (objects), JSON (arrays), JSONL or SQL INSERT under Output.
  4. Select Copy or Download.

Control how values are typed in the output

Whole numbers and decimals become JSON numbers, the lowercase words true and false become booleans, and empty cells become null. Everything else stays a string, including 1e5, $5, +5 and TRUE. Because digits are converted, a ZIP code such as 02134 becomes 2134, and integers above 9,007,199,254,740,991 lose their last digits. There is no switch to keep a column as text, so fix identifiers like these in your code or after conversion.

Fix quotes, thousands separators and duplicate headers

A value in double quotes may contain commas and line breaks, and a quote inside it is written as two quotes. A stray double quote inside an unquoted value starts a quoted section and can merge following rows, so quote the whole value and write each inner quote twice. A number such as 1,000 splits into two cells unless it is quoted. When two columns share a header, the last one wins, extra cells beyond the header are ignored and missing cells become null. Check the result with the JSON formatter.

Generate SQL INSERT statements from a table

Choose SQL INSERT and a Table field appears, which starts as my_table. Names are limited to letters, digits and underscores, with a leading underscore added before a digit. Each row becomes one INSERT with numbers as they are, TRUE, FALSE and NULL for those values, and text in single quotes with inner quotes doubled. Column names are not quoted, so rename headers such as order or group first. The output holds no CREATE TABLE statement, so make the table yourself.

Before you use the converted data

  • Check that Delimiter matches the file, especially for semicolon files from spreadsheets.
  • Look at the first object to confirm the keys came from the header row.
  • Check IDs, ZIP codes and phone numbers for lost leading zeros.
  • Rename SQL column headers that are reserved words, and create the table separately.

A table that only exists as a screenshot or photo can be read into CSV from the image, and one inside a PDF report can be pulled out as one CSV file per table, ready to paste here. To check or reshape the output, validate and re-indent the JSON, or draft the source table in Markdown with a live preview.

What you can do with Table to JSON

Review the main capabilities before you begin.

  • Convert CSV or TSV tables into JSON
  • Turn spreadsheet data into SQL INSERT statements
  • Export rows as JSONL for data pipelines
  • Paste Markdown or pipe tables and convert them
  • Use the first row as field names
  • Handle comma, semicolon or pipe delimiters

Settings reference

Available controls for Table to JSON.

Settings

DelimiterDropdown
Chooses how columns are split in your pasted table — comma, tab, semicolon, pipe, or Markdown pipes — or leave on Auto-detect to let the tool pick the separator from the first line.Options: Auto-detectCSV (Comma)TSV (Tab)SemicolonPipeMarkdown table
OutputDropdown
Picks the converted format: JSON objects keyed by column names, positional JSON arrays, one-record-per-line JSONL, or ready-to-run SQL INSERT statements.Options: JSON (objects)JSON (arrays)JSONLSQL INSERT
First row is headerOn / Off
When checked, the first row supplies the column names used as JSON keys or SQL columns; when unchecked, SQL columns are auto-named col_1, col_2 and JSON output falls back to positional value arrays.
TableText input
Sets the table name used in generated SQL INSERT statements (defaults to my_table); shown only when Output is SQL INSERT, and unsafe characters are automatically replaced with underscores.
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Frequently Asked Questions

How Table to JSON helps you get it done

Real problems it solves every day — for businesses, creators, and everyday tasks. Find the use case that fits you and start.

For Developers

CSV to API Migration

You have a legacy CSV export from a partner and need to POST it into a modern REST API expecting JSON. Convert, copy to your fetch body, and verify the shape — no glue script needed.

For Developers

Database Seeding

Generate ready-to-run SQL INSERT statements from a CSV of test data. Drop straight into your migration file or psql shell. The output handles strings, numbers, nulls and booleans correctly.

For Developers

BigQuery / Snowflake Ingestion

Cloud warehouses ingest JSONL faster than CSV. Convert your spreadsheet to JSONL and upload directly to BigQuery, Snowflake or Redshift staging.

Publishing

Markdown Documentation Tables

Convert a paste from your Markdown docs into JSON for programmatic processing — generate FAQ items, navigation entries, or pricing tier data from human-readable Markdown tables.

Productivity

Form Submission Analysis

Export your Google Forms or Typeform responses as CSV, convert to JSON, and run analytics or feed into your CRM via API. The header row becomes your field names.

For Developers

Static Site Data Generation

Feed table data into Next.js getStaticProps, Astro content collections or Hugo data files. JSONL is especially useful for content collections that map one row to one page.

For Developers

QA Test Fixture Generation

Paste a spreadsheet of test scenarios and export JSON fixtures or JSONL straight into a Jest, Pytest or Playwright test suite, skipping the hand-written mock-data file entirely.

For E-commerce

Supplier Catalog Bulk Import

Convert a supplier's price-list CSV into SQL INSERT statements for your products table, or JSON for a Shopify/WooCommerce bulk-import app, using the Table name field to target the exact table your store expects.

Productivity

No-Code Zapier & Airtable Sync

Turn an exported spreadsheet into the JSON array or object shape a Zapier webhook, Airtable automation or Make.com scenario expects, without writing a transformation script.

Finance

Bank Statement Reconciliation

Convert an exported bank or card-statement CSV into JSON for a personal-finance dashboard, or into SQL INSERT statements to load transactions straight into a ledger database.

Publishing

Static Site Data File Generation

Convert a spreadsheet of team bios, pricing tiers or product listings into a JSON data file that Hugo, Jekyll, Astro or Eleventy templates loop over directly, skipping the hand-written data/*.json file a JAMstack build usually requires.

Watch each transformation land

Every photo crosses the slash untouched and comes out the other side finished.