Plot settings
Example data table
| X | Y | Note |
|---|---|---|
| 0 | 1.2 | Start |
| 1 | 2.1 | Rising |
| 2 | 2.9 | Rising |
| 3 | 3.6 | Rising |
| 4 | 4.2 | Rising |
| 5 | 5.1 | End |
Formula used
The tool plots points on a Cartesian plane. Internally, charting converts each value into a position between the axis limits.
- xₚ = left + (x − xₘᵢₙ) / (xₘₐₓ − xₘᵢₙ) · width
- yₚ = top + (1 − (y − yₘᵢₙ) / (yₘₐₓ − yₘᵢₙ)) · height
- Optional linear regression uses least squares: m = Σ(x−x̄)(y−ȳ) / Σ(x−x̄)², b = ȳ − m·x̄.
How to use this tool
- Choose Manual pairs or Generate from function.
- For manual input, paste one x,y pair per line.
- Set labels, scale type, and any axis overrides.
- Turn on point markers, connecting lines, or regression.
- Submit to render the chart and summary above the form.
- Use CSV or PDF buttons to save the current result.
1) What an X–Y axis graph shows
An X–Y plot places each pair as a point on a Cartesian plane. The horizontal axis represents X values and the vertical axis represents Y values. When points rise as X increases, the relationship is positive; when they fall, it is negative. Outliers may signal unusual events or data entry errors.
2) Fast ways to enter accurate data
Paste pairs directly from a spreadsheet, one row per line. Use commas, tabs, spaces, or semicolons as separators, and enable “skip first row” if your first line is a header. Lines starting with a # are treated as comments and ignored. Use consistent units always for reliable comparisons.
3) Axis limits and readable scaling
Automatic limits use your smallest and largest values, which is ideal for quick checks. If you need consistent comparisons, lock the axis overrides so every chart shares the same min and max. This prevents the graph from “zooming” differently between runs. Add a small margin so points do not touch borders.
4) Linear trend line and fit quality
When regression is enabled, the tool computes the best‑fit line y = m·x + b using least squares. The slope m shows change in Y per one unit of X, while b estimates Y when X is zero. R² ranges from 0 to 1 and helps judge whether a straight line is useful.
5) Log scale for wide ranges
Logarithmic scaling is helpful when values span orders of magnitude, such as 0.1 to 10,000, because equal visual spacing represents multiplicative change. Because logarithms require positive numbers, all X and Y values must be greater than zero. If any value is zero or negative, use linear scaling or transform the dataset. Log scale can reveal hidden trends.
6) Connecting points and sorting by X
Connecting points is useful for time series and ordered measurements, where the path between observations matters. If your data arrives unsorted, enable “sort by X” before connecting. This avoids zig‑zag lines that jump back and forth across the axis. For scatter analysis, disable the line and focus on point patterns.
7) Saving results for reports
Use CSV export to reuse the cleaned pairs in other tools, share with colleagues, or archive a dataset version. Use PDF export for a quick one‑page summary including ranges, means, and the optional trend equation. You can also download a chart image for slides, notes, or documentation. Naming files by project and date supports clean comparisons.
FAQs
1) Why do some pasted rows disappear?
Rows with missing numbers, non‑numeric text, or fewer than two columns are skipped. Check your delimiter choice, remove extra symbols, and keep one X and one Y value per line.
2) What does “decimals” change?
It only changes how values are displayed in tables and summaries. Your original numbers are still used for plotting and calculations, so rounding here will not reduce the underlying input precision.
3) When should I use axis overrides?
Use overrides when you want comparable charts across different datasets, or when outliers stretch the axes too much. Setting fixed min and max limits can highlight the main cluster of points.
4) What does R² mean in simple terms?
R² indicates how closely the linear trend matches your points. Values near 1 mean points lie close to the line, while values near 0 mean the line explains little of the Y variation.
5) Can I plot negative values on log scale?
No. Log scaling requires positive X and Y values. If your data includes zero or negatives, switch to linear scale or transform the dataset before plotting.
6) How can I plot a smooth curve?
Use the function generator with a smaller step size to create more points. Then enable “connect points” to draw a continuous‑looking curve that follows the generated samples.