What columns does my sales data CSV need?
Two columns are enough: a label (month, region, product) and a number (revenue, units, target). Dates work as labels, and currency symbols are stripped automatically.
Monthly revenue, regional targets, product performance — sales data is almost always a clean label-and-number table, which is exactly what this converter expects.
Every template starts from a real dataset. Below is the exact CSV this page charts — download it, copy the rows, or swap in your own numbers.
This is the file this page charts. Upload it as-is, or copy the rows into a .csv and drop your own data in instead.
| Discount | Revenue_k |
|---|---|
| 5 | 62 |
| 10 | 78 |
| 15 | 95 |
| 20 | 112 |
| 25 | 131 |
| 30 | 148 |
| 35 | 152 |
| 40 | 149 |
| 45 | 141 |
| 50 | 128 |
Drop in your sales data CSV or Excel file. It is read in your browser and never uploaded to a server.
Labels and numbers are detected automatically — adjust a column type with one click if your scatter plot needs a different pairing.
Download the scatter plot as PNG, SVG or CSV, or open it in Studio to tune colors, labels and sorting.
A scatter plot is built for relationships: every row becomes a dot, and the cloud shape reveals correlation, clusters and outliers. For sales data, it exposes which two columns actually move together.
Two columns are enough: a label (month, region, product) and a number (revenue, units, target). Dates work as labels, and currency symbols are stripped automatically.
A scatter plot is built for relationships: every row becomes a dot, and the cloud shape reveals correlation, clusters and outliers. For sales data, it exposes which two columns actually move together.
CSV (comma, semicolon or tab separated), TSV, Excel workbooks (.xlsx, .xls, .ods) and ZIP archives containing CSV files — up to 100 MB per file. Everything is parsed in your browser.
Upload a file, confirm the columns, and your scatter plot appears instantly — nothing leaves your browser.
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