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pca: A Python Package for Principal Component Analysis.

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PCA correlation matrix plot, sorted by similarity, might be good to see which variable has most effect in PC0/PC1. https://www.reneshbedre.com/blog/principal-component-analysis.html#perform-pca-using-scikit-learn P.S. Multicollinearity Graphs are useful, but they are not quite...

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![image](https://user-images.githubusercontent.com/109609332/179778447-4b280c4a-39cc-448d-ab05-5339b990ed31.png) How do I fix this?

Hi Erdogant, How could it be possible to compute DMODX in PLS? Thanks Pablo

Sometimes the base columnar data might not be normally distributed (bell curve) or continuously uniform (quantile-esque). Guides on Power Transform (Yeo-Johnson vs Box-Cox): - https://en.wikipedia.org/wiki/Power_transform - https://statisticaloddsandends.wordpress.com/2021/02/19/the-box-cox-and-yeo-johnson-transformations-for-continuous-variables/ - https://jsmp.dk/posts/2019-08-23-transformingdata/ Library...

In https://erdogant.github.io/pca/pages/html/pca.pca.html It says `pca.pca.pca(n_components=0.95, n_feat=25, method='pca', alpha=0.05, n_std=2, onehot=False, normalize=False, detect_outliers=['ht2', 'spe'], random_state=None, verbose=3)` `n_components` is not an integer like `hotellingsT2` but instead something similar to `alpha`, but neither...

I have found edge cases that transforming new unseen data will change the results in the 'outliers' dataframe on the original data used in fit, even with update_outlier_params=False. This specifically...

As I see, there is no way of scaling the biplot axes with the variance of the components as in e.g. R biplot.prcomp ([see here](https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/biplot.princomp)). This is really important, since...

Typo in pca.py#L970 and pca.py#L1401: It should be "principal" not "principle".

Hi @erdogant, Thank you for providing this library. It's exactly what I've been looking for. It would be great to have this installable through conda-forge. Would you be interested in...

pca v2.0.4 not producing the expected graphs and producing errors. See google colab: https://colab.research.google.com/drive/1UTets1alPB1tcA_wpKAKBd_14nENqoXX?usp=sharing I tried solving this by installing different versions of matplotlib and python versions but to no...