See Which Metrics Move Together In Minutes

How it works

For every pair of your selected columns, the analysis computes the Pearson correlation coefficient (r) — a -1 to +1 score of how tightly the two move together — plus a significance test of whether that relationship could be chance. The heatmap shows the full matrix, the table ranks the strongest pairs, and the scatter shows the dominant relationship's actual shape.

Use it when you have several numeric columns and want a fast map of what relates to what — before regression, forecasting, or dashboard pruning.

Not for categorical columns (use the categorical association tool) and blind to non-linear patterns — always sanity-check the scatter.

What data do you need?

Any table with several numeric columns. For example, weekly business metrics:

Minimum 10 rows · Best with 50-10,000 rows and 3-12 numeric columns

What's in the report?

Standard-library analysis: pairwise correlations across the numeric columns you choose. A full correlation heatmap, the strongest relationships ranked with significance tests, and a scatter of the single strongest pair — so you can see which metrics move together, how tightly, and whether it's statistically real. Works on any dataset: map 2 or more numeric columns.