Highlights
In Diagnosis, you can now generate 2d principal component graphs. This can help you visualize higher dimensional data.
python
dia = DIA(df)
dia.plot_pc2(pl.all().exclude("species"), by = "species")
In addition, the following PCA related queries are available:
df.select(
pds.query_pca("a", "b") singular values and weight vectors
).unnest("a")
df.select(
pds.query_singular_values("a", "b", center = True, as_explained_var=True)
)
The Xi - Correlation is also implemented:
df.select(
pds.xi_corr("x", "y")
)
What's Changed
* try new maturin config by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/128
* added basic pca exprs by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/129
* added infer_prob by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/131
* More pca by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/132
* xi_corr by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/134
**Full Changelog**: https://github.com/abstractqqq/polars_ds_extension/compare/v0.4.1-release...v0.4.2
v0.4.1-release
[Original release note](https://github.com/abstractqqq/polars_ds_extension/releases/tag/v0.4.1)
What's Changed
* upgraded download action in CI by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/124
* removed unncessary test-deps by abstractqqq in https://github.com/abstractqqq/polars_ds_extension/pull/126
**Full Changelog**: https://github.com/abstractqqq/polars_ds_extension/compare/v0.4.1-fix-release...v0.4.1-release
v0.4.1-fix-release