Copulogram
This package is provides a new data visualisation tool to explore multivariate datasets developped with V.Chabridon.
A copulogram is an innovative plot as it decomposes a mutivariate dataset between the effects of the marginals and those of the dependence between features. To do so, it represents the marginals with univariate kernel density estimation plots or histograms (diagonal), and the dependence structure with scatter plots in the ranked space (upper triangle). On the bottom triangle the scatter plots are set in the physical space, gathering the effects of the marginals and the dependencies. Since the dependence structure is theoretically modeled by an underlying copula, this plot is called copulogram, generalizing the well-known ``correlogram'' to nonlinear dependencies. It gives a synthetic and empirical decomposition of the dataset.
Copulogram of a wind-wave dataset
Installation
The following commands install the current version of the copulogram package.
~$ pip install copulogram
Example on iris dataset
Using the famous iris dataset, let us plot copulograms with different settings:
>>> import seaborn as sns
>>> import copulogram as cp
>>> data = sns.load_dataset('iris')
>>> copulogram = cp.Copulogram(data)
>>> copulogram.draw()
>>> copulogram.draw(alpha=0.8, hue='species', kde_on_marginals=False)
>>> copulogram.draw(hue='species', quantile_contour_levels=[0.2, 0.4, 0.6, 0.8])
References
-
Empirical Bernstein copula: Sancetta, A., & Satchell, S. (2004). The Bernstein Copula and Its Applications to Modeling and Approximations of Multivariate Distributions. Econometric Theory, 20(3), 535–562.
-
Nonparametric copula estimation: Nagler, T., Schellhase, C. & Czado, C. (2017). Nonparametric estimation of simplified vine copula models: comparison of methods. Dependence Modeling, 5(1), 99-120.
-
OpenTURNS: Baudin, M., Lebrun, R., Iooss, B., Popelin, A.L. (2017). OpenTURNS: An Industrial Software for Uncertainty Quantification in Simulation.
-
Wind-waves environmental dataset: The data was generated by a numerical model from ANEMOC (Digital Atlas of Ocean and Coastal Sea States, see http://anemoc.cetmef.developpement-durable.gouv.fr/)
Metadata
Release files for copulogram 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| copulogram-0.0.4.tar.gz | 19.2 kB | Without provenance | Details for copulogram-0.0.4.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| copulogram-0.0.4-py3-none-any.whl | Python 3 | none | any | Details for copulogram-0.0.4-py3-none-any.whl |
Total release size: 39.3 kB
Release files / copulogram-0.0.4.tar.gz
| Download URL | copulogram-0.0.4.tar.gz |
|---|---|
| Size | 19.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d826a2cf553d42cccb30988f9c1adb54ec3a7368651789178147db29f4e00a6b
|
|
BLAKE2b-256 checksum How to use checksums |
1d3c30fb0af7d86cd2cf628530c0bda39986f1feab4ccfca63abe0efeb4fae0c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / copulogram-0.0.4-py3-none-any.whl
| Download URL | copulogram-0.0.4-py3-none-any.whl |
|---|---|
| Size | 20.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ed1f2888606ddcf18c7b0738520d0a3809865344711926efad241ec52860027d
|
|
BLAKE2b-256 checksum How to use checksums |
0cc38c1f91f607813afce8f7adbf900b404e8491b4d361ed81775f961846e579
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Security for copulogram 0.0.4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.