FAQ

Can I import CSV files from any website?

Yes, as long as the CSV file is publicly accessible via a direct URL. You can import from public servers, Google Drive (with a shareable link), API endpoints, or anywhere else online. The URL must point directly to the CSV file, not a webpage or landing page.

How do I import a CSV from Google Drive?

Right-click the CSV file in Google Drive, select "Share," change the setting to "Anyone with the link," and set the role to "Viewer." Copy the shareable link and paste it into Coupler.io. Do NOT use the regular Google Drive URL—it won't work with Coupler.io.

Can I filter my CSV before importing (e.g., by date range)?

It depends on your CSV source. If your source is an API endpoint that supports query parameters or POST filters (e.g., Clockify, analytics platforms), use the "URL query parameters" or "Request body" fields to specify filters. If your CSV is a static file, you'll need to clean it up after import using formulas in your destination.

What HTTP method should I use?

Most public CSV files use GET. However, some sources (like Clockify's CSV export API) require POST. Check your CSV source's documentation. If unsure, start with GET; if it fails with a "405 Method Not Allowed" error, switch to POST.

Do I need to provide authentication to import a CSV?

Only if your CSV source requires it. Public CSVs don't need authentication. If your source is an API endpoint or protected file, add authentication headers (e.g., Authorization: Bearer YOUR_TOKEN) in the "HTTP request headers" field.

Can I append multiple CSV imports into one sheet?

Yes. Create separate data flows for each CSV source, and use Append mode on each. Coupler.io will add new rows below existing data each time it runs. This is great for consolidating time-series data or reports from multiple accounts.

What's the difference between Replace and Append mode?

Replace mode overwrites all data each refresh (good for current-state snapshots). Append mode adds new rows below existing data (good for historical tracking). You can choose the mode when setting up your destination in the data flow.

How often can I refresh my CSV import?

You can schedule refreshes as frequently as every 15 minutes (depending on your plan). However, refresh only as often as your CSV source updates. Refreshing more frequently than your source changes is wasteful and may hit rate limits.

Can I transform or reformat my CSV data during import?

Coupler.io imports CSV data as-is. To transform or reformat, use Google Sheets formulas, BigQuery queries, or another transformation tool. You can also use Coupler.io's Join, Append, and Aggregate transformations if combining multiple CSV sources or entities.

What should I do if I get a "CSV parse error: Invalid Opening Quote" message?

This error usually means the CSV has unescaped quotes or special characters. Download the CSV file locally, open it in a text editor, and check the formatting. Properly formatted CSVs use consistent delimiters and escape internal quotes. If the source file is malformed, contact your CSV provider and ask them to export with proper escaping. Alternatively, try the "Ignore quotes" option in advanced settings.

Can I import a CSV from an FTP server?

Support for FTP is limited. If your FTP server has a public URL or allows HTTP access, use that URL in Coupler.io. If credentials are required, include them in the URL (e.g., ftp://username:[email protected]/file.csv) or as headers.

Why is my import showing fewer rows than expected?

Check the "Skip rows" setting—if set too high, you may skip data. Also verify that your CSV source returned all expected data (test the URL directly). If using filters, confirm they're not excluding rows. Finally, ensure the CSV isn't too large; Google Sheets has a 10 million cell limit.

Can I send my CSV data to BigQuery or Looker Studio instead of Google Sheets?

Yes. When setting up your data flow, choose BigQuery, Looker Studio, or any other supported destination. CSV imports work with Google Sheets, Excel, BigQuery, Looker Studio, and AI platforms (Claude, ChatGPT, Gemini, etc.). BigQuery is great for very large CSVs that exceed Google Sheets' row limits.

For more detailed troubleshooting, see Common Issues. For optimization tips, check out Best Practices.