add dbt_pca package

[dwreeves]

Description

dbt_pca is an easy way to perform principal component analysis (PCA) in SQL using dbt. Example:

{{
  config(
    materialized="table"
  )
}}
select * from {{
  dbt_pca.pca(
    table=ref('collinear_matrix'),
    index='idx',
    columns=['x1', 'x2', 'x3', 'x4', 'x5'],
    ncomp=2
  )
}} as pca

comp	col	eigenvector	eigenvalue	coefficient
0	x1	0.23766561884860857	29261.18329671314	40.6548443559801
0	x2	-0.5710963390821377	29261.183296713134	-97.69117169801471
0	x3	-0.5730424984614262	29261.18329671314	-98.02407978560524
0	x4	-0.5375734671620216	29261.18329671314	-91.9567825723166
0	x5	0.0010428157925962138	29261.183296713138	0.17838303220022225
1	x1	-0.0662409860256577	10006.031828705965	-6.626096072806324
1	x2	-0.001674528192609409	10006.031828705967	-0.16750331398380647
1	x3	-0.0027280948128929504	10006.031828705962	-0.27289174588904075
1	x4	-0.022663548107992145	10006.031828705964	-2.2670382209597086
1	x5	0.9975411013143917	10006.031828705964	99.78419058137138

Link to your package's repository:

Checklist

First run experience

• (Required): The package includes a licence file detectable by GitHub, such as the Apache 2.0 or MIT licence.
• The package includes a README which explains how to get started with the package and customise its behaviour
• The README indicates which data warehouses/platforms are expected to work with this package

Customisability

• The package uses ref or source, instead of hard-coding table references.

Packages for data transformation (delete if not relevant):

• provide a mechanism (such as variables) to customise the location of source tables.
• do not assume database/schema names in sources.

Dependencies

Dependencies on dbt Core

• The package has set a supported require-dbt-version range in dbt_project.yml. Example: A package which depends on functionality added in dbt Core 1.2 should set its require-dbt-version property to [">=1.2.0", "<2.0.0"].

Dependencies on other packages defined in packages.yml:

• Dependencies are imported from the dbt Package Hub when available, as opposed to a git installation.
• Dependencies contain the widest possible range of supported versions, to minimise issues in dependency resolution.
• In particular, dependencies are not pinned to a patch version unless there is a known incompatibility.

Interoperability

• The package does not override dbt Core behaviour in such a way as to impact other dbt resources (models, tests, etc) not provided by the package.
• The package uses the cross-database macros built into dbt Core where available, such as {{ dbt.except() }} and {{ dbt.type_string() }}.
• The package disambiguates its resource names to avoid clashes with nodes that are likely to already exist in a project. For example, packages should not provide a model simply called users.

Versioning

• (Required): The package's git tags validates against the regex defined in hubcap/version.py (examples).
• The package's version follows the guidance of Semantic Versioning 2.0.0. (Note in particular the recommendation for production-ready packages to be version 1.0.0 or above)

[joellabes]

🚀