trend: algorithms for detecting trends in time-series data
What is trend?
trend is a python package for detecting trends in time-series data. It’s design and documention borrow heavily from the R package known as trend developed by Thorsten Pohlert.
More documentation is forthcoming, but for now, refer to the source.
1 maintainer
Metadata
1 maintainer
Release files for trend 0.1
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 | Actions |
|---|---|---|---|---|
| trend-0.1.tar.gz | 8.1 kB | Without provenance | Details for trend-0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| trend-0.1-py3-none-any.whl | Python 3 | none | any | Details for trend-0.1-py3-none-any.whl |
Total release size: 17.4 kB
Release files / trend-0.1.tar.gz
| Download URL | trend-0.1.tar.gz |
|---|---|
| Size | 8.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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twine/1.12.1 pkginfo/1.4.2 requests/2.19.1 setuptools/40.4.3 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.3
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Release files / trend-0.1-py3-none-any.whl
| Download URL | trend-0.1-py3-none-any.whl |
|---|---|
| Size | 9.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.12.1 pkginfo/1.4.2 requests/2.19.1 setuptools/40.4.3 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.3
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Security for trend 0.1
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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