* Improved speed in plotting in case of having thousands of samples by setting parameter `label=None`
`model.biplot(label=None) `
1.7.0
* Density coloring implemented with the `gradient `parameter.
In this example, the `cmap=Set1 `will be used to color the class labels. The coloring will have a continuous scale towards the borders.
`pca.scatter(cmap='Set1', gradient='ffffff') `
1.6.4
* Title can be changed in the figures * Fix when normalizing out PCs by the conversion of dataframe into a numpy array.
1.6.3
* Fix for newer versions of Python related to dict_items. Thanks tgy! * Fix in case no explained variance is detected.
1.6.2
* The .plot functionality will show the total explained variance across the components when selecting on explained variance: n_components<1 * docstring updates * Some code cleaning
1.6.1
* Fixes for biplot when choosing different PC to plot. * New parameter for biplot, to color the arrow: `model.biplot(color_arrow='g')`