wheely-mammoth is a Python library for reading and handling extremely large proteomics datasets with PySpark. It provides a simple way to find and describe datasets for use with other tools.
Installation
wheely-mammoth requires Python 3.8+ and can be installed with pip
pip install wheely-mammoth
Basic Usage
Example usage:
>>> from wheely.mammoth.parsers import read_encyclopedia_features
>>> ds = read_encyclopedia_features("data/*.features.txt")
>>> type(ds)
<class 'wheely.mammoth.dataset.PsmDataset'>
>>> ds.scores.select(ds.score_columns[0]).describe().toPandas()
summary primary
0 count 1770
1 mean 12.408585019887022
2 stddev 3.727298477605115
3 min 6.9876947
4 max 43.78316
Metadata
Release files for wheely-mammoth 0.17.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| wheely_mammoth-0.17.0.tar.gz | 2.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| wheely_mammoth-0.17.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.8 MB
Release files / wheely_mammoth-0.17.0.tar.gz
| Download URL | wheely_mammoth-0.17.0.tar.gz |
|---|---|
| Size | 2.8 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Download URL | wheely_mammoth-0.17.0-py3-none-any.whl |
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| Size | 41.6 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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