A method to detect outliers in a given data with the help of interquartile range.
1 maintainer
Metadata
1 maintainer
Release files for outlier-simran 0.0.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| outlier_simran-0.0.1.tar.gz | 2.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| outlier_simran-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.3 kB
Release files / outlier_simran-0.0.1.tar.gz
| Download URL | outlier_simran-0.0.1.tar.gz |
|---|---|
| Size | 2.4 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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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3
|
Release files / outlier_simran-0.0.1-py3-none-any.whl
| Download URL | outlier_simran-0.0.1-py3-none-any.whl |
|---|---|
| Size | 2.9 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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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3
|
Security for outlier-simran 0.0.1
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