hhpy - Data Science convenience project
Built with Python Package Template Project.
My attempt at creating a convenient way to use different data science and machine learning operations and frameworks using one unified way. The main idea is to store data in pandas DataFrames and start from there.
Also provides several extensions on pandas, matplotlib and seaborn for convenience.
Installing
Install and update using pip:
pip install hhpy
Or get the latest dev version from github
pip install git+https://github.com/rhedak/hhpy
Documentation
Documentation is available at https://hhpy.readthedocs.io/
1 maintainer
Release files for hhpy 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hhpy-0.3.1.tar.gz | 139.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hhpy-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 238.1 kB
Release files / hhpy-0.3.1.tar.gz
| Download URL | hhpy-0.3.1.tar.gz |
|---|---|
| Size | 139.2 kB |
| Tags | Source |
|
SHA-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/4.0.2 CPython/3.9.16
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Release files / hhpy-0.3.1-py3-none-any.whl
| Download URL | hhpy-0.3.1-py3-none-any.whl |
|---|---|
| Size | 98.9 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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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
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