Visualize high-dimensional data instantly. Plotivy calculates Principal Components, plots scores and loadings, and draws confidence ellipses automatically.
Calculating eigenvectors and eigenvalues manually or in Excel is a nightmare. You just want to see the plot.
Overlaying loading vectors (arrows) on top of score points with correct scaling is difficult in standard plotting tools.
Drawing 95% confidence ellipses for your groups usually requires advanced statistical packages or custom scripts.
Upload your multivariate dataset (e.g., gene expression, chemical composition, survey data).
"Perform PCA. Plot PC1 vs PC2. Color by 'Group' and add confidence ellipses."
Download the plot and the explained variance table.
✨ Plotivy AI uses scikit-learn and matplotlib to perform the analysis and visualization.
Visualize your data in 2D (PC1 vs PC2) or interactive 3D (PC1 vs PC2 vs PC3) to find hidden clusters.
Understand which variables drive the variation. Overlay loading vectors to see feature contributions.
Automatically generate scree plots to decide how many principal components to retain.
Combine PCA with K-means clustering to automatically identify and color groups in your data.