SmartQueryTools

Combine Columns in JSON Files Online

Combine multiple columns into one in JSON files directly in your browser. Merge first name and last name, join address fields, or concatenate any columns with a custom separator — no upload required.

How to combine Columns in JSON files

  1. Drop your file onto the upload area. The first two columns are ticked by default and the output name is set to both names joined by an underscore.
  2. Tick the columns to combine in the order you want them joined. Each ticked column shows its position (#1, #2, and so on), and the order follows your clicks, not the file's column order.
  3. Type the separator, such as a space, ", " or " - ", and set the output column name.
  4. Tick Remove source columns if you only want the combined column, then click Combine Columns.
  5. Check the preview and download the file in the same format.

Your file is processed locally in your browser and is never uploaded. The free limit is 50 MB per file; larger files work if your device has the memory for them.

Worked example

An international order export stores the delivery address across four columns. The courier's upload form wants one address line per parcel.

Input (JSON)

[
  {
    "recipient": "Priya Shah",
    "street": "12 Cuba Street",
    "city": "Wellington",
    "postcode": "6011",
    "country": "New Zealand"
  },
  {
    "recipient": "Tom Walsh",
    "street": "8 Quay Road",
    "city": "Cork",
    "postcode": null,
    "country": "Ireland"
  },
  {
    "recipient": "Ines Duarte",
    "street": "Rua Augusta 40",
    "city": "Lisboa",
    "postcode": "1100-048",
    "country": "Portugal"
  }
]

Settings

  • Columns, in click order: street, city, postcode, country
  • Separator: ", "
  • Output column name: full_address
  • Remove source columns: ticked

Result

recipientfull_address
Priya Shah12 Cuba Street, Wellington, 6011, New Zealand
Tom Walsh8 Quay Road, Cork, Ireland
Ines DuarteRua Augusta 40, Lisboa, 1100-048, Portugal

Values are joined in the order the columns were ticked, with the separator between them. Tom's postcode is empty, and it is skipped along with its separator, so there is no ", ," gap. With the source columns removed, full_address takes the position of the last source column. Unticked columns such as recipient stay where they were.

Working with JSON files

Only top-level keys can be ticked. Numbers and booleans are converted to text, so {"floor": 3, "unit": "B"} joined with "-" gives "3-B". A nested object or array can also be ticked, but it is turned into text such as {'city': Cork} or [a, b], which is rarely what you want. Flatten the JSON first and combine the flat fields instead. Strings are joined without their JSON quotes, so "Cork" and "Ireland" give Cork, Ireland.

Objects that lack a key are treated as NULL for that key and skipped when joining. If every ticked key is missing or null in an object, the combined value is an empty string rather than null. The new key is added after the existing keys, or in place of the last ticked key when sources are removed. The combined value is always written as a JSON string.

Frequently Asked Questions

What happens when some JSON objects are missing a key I am combining?

The missing key is treated as null and skipped along with its separator. The other values are still joined.

Can I combine nested JSON fields?

Only after flattening. Ticking a nested object joins its whole text form. Flatten the file so each nested field is its own key, then combine those keys.

What happens to empty (null) values when combining columns?

They are skipped, and so is the separator next to them. Combining "Cork", null and "Ireland" with ", " gives "Cork, Ireland". Empty strings are not null, so they are joined as-is.

Can I combine more than two columns, and control the order?

Yes. Tick as many columns as you need. They are joined in the order you tick them, shown as #1, #2 and so on next to each column name.

Can I leave the separator empty?

Yes. With an empty separator the values are joined directly, for example "AB" and "123" become "AB123".

Related Tools

Deduplicate JSON Files Online

Remove duplicate rows from JSON files instantly in your browser. No upload, no server — 100% private.

Hash & Anonymise Columns in JSON Files Online

Anonymise or pseudonymise columns in JSON files by replacing values with MD5, SHA-256, or DuckDB hashes — directly in your browser. Useful for GDPR compliance and sharing data without exposing PII — no upload required.

Rename Columns in JSON Files Online

Rename columns in JSON files instantly in your browser. No upload, no server — your data stays on your device.

Combine Columns in CSV Files Online

Combine multiple columns into one in CSV files directly in your browser. Merge first name and last name, join address fields, or concatenate any columns with a custom separator — no upload required.

Combine Columns in Excel Files Online

Combine multiple columns into one in Excel files directly in your browser. Merge first name and last name, join address fields, or concatenate any columns with a custom separator — no upload required.

Combine Columns in Parquet Files Online

Combine multiple columns into one in Parquet files directly in your browser. Merge first name and last name, join address fields, or concatenate any columns with a custom separator — no upload required.

JSON Viewer Online

View and inspect JSON files directly in your browser. Browse rows, check column names and data types — no upload required, your data stays on your device.

Convert JSON to Parquet Online

Convert JSON files to Parquet format directly in your browser. No upload required — your data never leaves your device.