Correlation Matrix Explorer 2D: Heatmap & Pair-Plot Lab

Data scientists reach for a correlation heatmap the moment a new table lands on their desk — one glance shows which columns move together, which move oppositely, and which carry no linear relationship at all. This 2D simulator generates a five-variable synthetic dataset with a known ground-truth correlation structure, renders the empirical Pearson correlation matrix as a flat, clickable heatmap, and draws the raw scatter behind whichever pair you select so the connection between "points on a scatter plot" and "one coloured cell in a heatmap" is never abstract. Drag the target-correlation slider to strengthen or reverse the relationship between variables A and B, add measurement noise to watch the classic regression-dilution effect shrink the observed r below its true value, click through all ten unique variable pairs to compare their scatters side by side, and resample to see how much a correlation matrix jitters from one dataset draw to the next at a given sample size — exactly the judgment call behind reading real exploratory-data-analysis output from Seaborn, Plotly or matplotlib.