CSV Operations Query Tool Online: Filter, Dedupe, Compare CSV and Excel

What is a CSV operations tool?

A CSV operations tool is a lightweight query surface for spreadsheet-like data. Instead of opening Excel, writing SQL, or creating a one-off Python script, you paste a CSV file and run commands such as where(status == "active"), unique(email), countBy(category), or compare(source_id, target_id). It is useful when the file is structured enough to query but not important enough to build a whole import pipeline.

How to use CSV Operations

CSV query examples

The CSV query language is intentionally small. It focuses on everyday data cleanup tasks, not full SQL. These commands cover most CSV and Excel analysis workflows.

Filter CSV online

Filtering is the fastest way to turn a large export into a short answer. Use where() for column comparisons and search() for a broad text search. For example:

where(status == "active")
where(amount > 100)
where(owner contains "platform")
search(invoice)

This is useful for support exports, billing files, operational reports, and one-off investigations where opening a full spreadsheet is slower than asking a direct question.

Dedupe CSV and find duplicates

Duplicate values are common in email lists, customer exports, inventory feeds, and database snapshots. CSV Operations gives you three related commands:

• unique(email) returns distinct values.
• duplicates(email) shows repeated values and counts.
• dedupe(email) keeps one row per unique value.

Compare CSV columns

Comparing columns is helpful when you have two ID lists in the same file: imported IDs vs exported IDs, source vs target, allowlist vs observed values, or previous vs current identifiers. Use compare(left_id, right_id) to return each value with a status: both, left-only, or right-only.

Run formulas and numeric summaries

For quick math, use summary functions such as sum(cost), avg(cost), min(cost), and max(cost). You can also run row-wise formulas over numeric columns, for example price * quantity or subtotal + tax. This is not a full spreadsheet engine, but it is enough for quick totals, validation, and sanity checks.

CSV Operations vs CSV Preview

Spoold has two CSV-focused tools because the workflows are different.

Large CSV and Excel files

Large CSV files can lock up a browser if every edit triggers parsing, type analysis, suggestions, and query execution. CSV Operations avoids that by using a manual Run query flow for large inputs. The input can still be pasted or uploaded, but expensive operations wait until you click Run. For very large data sets, start with columns() or head(20)before running broad queries such as rows(), sortBy(), orsimilar().

Privacy: client-side CSV analysis

CSV Operations runs in your browser. Pasted data and uploaded files are processed locally by the page, which makes it practical for quick investigations where you do not want to send a spreadsheet to a server. If your organization has strict data-handling rules, still follow those policies, but the tool itself is designed as a client-side utility.

FAQ

Related tools

For conversion and exports, open CSV Preview. For operations on converted JSON, use JSON Operations. For pretty-printing JSON output, use the JSON Formatter. For a deeper conversion walkthrough, read the CSV to JSON conversion guide.