modelframe
Compute fixed and random effects model matrices in Python
About
modelframe builds model matrices and response vectors from a given dataset using lme4-style formulas in Python.
Installation
You can install modelframe either from PyPI using:
pip install modelframeor using the latest GitHub [release](https://github.com/dirmeier/modelframe/releases/):
python -m pip install git+https://github.com/dirmeier/modelframe.git@v0.1.01 maintainer
Metadata
1 maintainer
Release files for modelframe 0.1.1
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 | |
|---|---|---|---|---|
| modelframe-0.1.1.tar.gz | 6.3 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| modelframe-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 27.6 kB
Release files / modelframe-0.1.1.tar.gz
| Download URL | modelframe-0.1.1.tar.gz |
|---|---|
| Size | 6.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.6
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Release files / modelframe-0.1.1-py3-none-any.whl
| Download URL | modelframe-0.1.1-py3-none-any.whl |
|---|---|
| Size | 21.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.6
|
Security for modelframe 0.1.1
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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