Pca

Latest version: v2.0.7

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1.7.1

* 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')`

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