Ride History Visualizer Upload your Uber / Lyft export and see your ride spending trends instantly

Why doesn't Uber or Lyft give you a spending trend chart?

The built-in "ride history" screens in both the Uber and Lyft apps are just a plain list — no summary charts at all. If you want to know how much you spent on rides each month, or which month was unusually expensive, you're stuck manually adding it up or building your own spreadsheet. Ride History Visualizer solves this small but recurring pain point: upload the CSV export you got from the official "Download my data" request, and within seconds you'll see a monthly spending trend chart, total spend, total rides, and average fare — plus a date range filter for any specific month or trip.

Where does the calculation happen? Is my data uploaded anywhere?

No. This tool works entirely on an "upload file → compute in browser → view charts" model. No account is required, and your file content is never sent to any server — you can verify this yourself by opening your browser's DevTools Network panel; there's simply no outgoing request carrying your data. You can safely analyze your real ride history, and once you close the tab, nothing is kept anywhere.

Uber and Lyft export formats differ — how does the tool tell them apart?

The tool automatically detects whether you uploaded a Uber or Lyft export based on column name patterns (for example Uber's common "Begin Trip Time" / "Trip or Order Status", or Lyft's common "Ride Type"), and shows the detection result on screen for you to confirm. If the official export format has changed and can't be clearly identified, the tool still tries to locate date and amount columns for a generic analysis, and reminds you to double-check the numbers. If parsing fails altogether, you'll get a clear checklist instead of a blank page.

This tool never connects to Uber or Lyft's official account APIs in real time, and never stores any data in a database or backend — you must first download the export file yourself through official channels, then upload it here for a purely browser-side visualization.