CSV Viewer

How the viewer works

Paste CSV into the input area and click Parse. The viewer reads the first row as column headers and renders every subsequent row as a table row. Columns are sortable by clicking the header. Pagination keeps the browser responsive on files with thousands of rows — only one page of rows is in the DOM at a time.

This is useful for quickly inspecting a CSV export before transforming it with another tool. Viewing the raw structure first tells you whether the column count is consistent, whether the header names match what a downstream import expects, and whether any rows contain obviously wrong values. Catching a structural problem at this stage avoids a confusing error later in a pipeline.

When to use the viewer

Checking that column headers are correct before a database import is one of the most common uses. If the CSV has a column named "email_address" but your import script expects "email", the import will silently produce empty fields. Viewing the header row takes five seconds and removes the guesswork.

Verifying that a CSV export has the expected row count is another good use. If you exported 1,200 records from a CRM and the viewer shows 1,198 rows, two records failed to export or were filtered out somewhere. That discrepancy is worth investigating before the file goes into a reporting tool.

Spotting blank cells or misaligned columns caused by unescaped commas is harder to catch by scanning raw text. The table layout makes it immediately obvious when a row has more columns than the others, which points to an unescaped comma inside a text field.

Delimiter handling

CSV files can use commas, semicolons (common in European locales where commas are used as decimal separators), or tabs as the field delimiter. The viewer tests each delimiter against the first line of the file and picks whichever produces the most consistent column count. If auto-detection picks the wrong delimiter, you can override it in the settings before re-parsing.

If detection fails entirely, the raw line appears as a single column. This usually means the file uses an unusual delimiter like a pipe character. In that case, use the CSV Editor to do a find-and-replace on the delimiter before pasting into the viewer.

Frequently asked questions