Metadata-Version: 2.1
Name: timeseriesflattener
Version: 0.13.0
Summary: A package for converting time series data from e.g. electronic health records into wide format data.
Author: Martin Bernstorff
Requires-Python: >=3.9,<3.11
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Dist: SQLAlchemy (>=1.4.41,<1.5.42)
Requires-Dist: catalogue (>=2.0.0,<2.1.0)
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Requires-Dist: frozendict (>=2.3.4,<2.4.0)
Requires-Dist: numpy (>=1.23.3,<1.23.6)
Requires-Dist: pandas (>=1.4.0,<1.6.0)
Requires-Dist: protobuf (<=3.20.3)
Requires-Dist: psutil (>=5.9.1,<6.0.0)
Requires-Dist: psycopmlutils (>=0.2.4,<0.3.0)
Requires-Dist: pyarrow (>=9.0.0,<9.1.0)
Requires-Dist: pydantic (>=1.9.0,<1.10.0)
Requires-Dist: pyodbc (>=4.0.34,<4.0.36)
Requires-Dist: scikit-learn (>=1.1.2,<1.1.3)
Requires-Dist: scipy (>=1.8.0,<1.9.4)
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Requires-Dist: wandb (>=0.12.0,<0.13.5)
Requires-Dist: wasabi (>=0.9.1,<0.10.2)
Description-Content-Type: text/markdown

<a href="https://github.com/Aarhus-Psychiatry-Research/timeseriesflattener"><img src="https://github.com/Aarhus-Psychiatry-Research/timeseriesflattener/blob/main/docs/_static/icon.png?raw=true" width="220" align="right"/></a>

# Time-series Flattener

![python versions](https://img.shields.io/badge/Python-%3E=3.10-blue)
[![Code style: black](https://img.shields.io/badge/Code%20Style-Black-black)](https://black.readthedocs.io/en/stable/the_black_code_style/current_style.html)
[![github actions pytest](https://github.com/Aarhus-Psychiatry-Research/timeseriesflattener/actions/workflows/main_test_and_release.yml/badge.svg)](https://github.com/Aarhus-Psychiatry-Research/timeseriesflattener/actions)
[![PyPI version](https://badge.fury.io/py/timeseriesflattener.svg)](https://pypi.org/project/timeseriesflattener/)

## Roadmap
Roadmap is tracked on our [kanban board](https://github.com/orgs/Aarhus-Psychiatry-Research/projects/11/views/1).

## 🔧 Installation
To get started using timeseriesflattener simply install it using pip by running the following line in your terminal:

```
pip install timeseriesflattener
```

## 📖 Documentation

| Documentation          |                                                                                              |
| ---------------------- | -------------------------------------------------------------------------------------------- |
| 🎛 **[API References]** | The detailed reference for timeseriesflattener's API. Including function documentation |
| 🙋 **[FAQ]**            | Frequently asked question                                                                    |

[api references]: https://Aarhus-Psychiatry-Research.github.io/timeseriesflattener/
[FAQ]: https://Aarhus-Psychiatry-Research.github.io/timeseriesflattener/faq.html

## 💬 Where to ask questions

| Type                           |                        |
| ------------------------------ | ---------------------- |
| 🚨 **Bug Reports**              | [GitHub Issue Tracker] |
| 🎁 **Feature Requests & Ideas** | [GitHub Issue Tracker] |
| 👩‍💻 **Usage Questions**          | [GitHub Discussions]   |
| 🗯 **General Discussion**       | [GitHub Discussions]   |

[github issue tracker]: https://github.com/Aarhus-Psychiatry-Research/timeseriesflattener/issues
[github discussions]: https://github.com/Aarhus-Psychiatry-Research/timeseriesflattener/discussions


## 🎓 Projects
PSYCOP projects which use `timeseriesflattener`. Note that some of these projects have yet to be published and are thus private.

| Project                 | Publications |                                                                                                                                                                                                                                       |
| ----------------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **[Type 2 Diabetes]**   |              | Prediction of type 2 diabetes among patients with visits to psychiatric hospital departments                                                                                                                                          |
| **[Cancer]**            |              | Prediction of Cancer among patients with visits to psychiatric hospital departments                                                                                                                                                   |
| **[COPD]**              |              | Prediction of Chronic obstructive pulmonary disease (COPD) among patients with visits to psychiatric hospital departments                                                                                                             |
| **[Forced admissions]** |              | Prediction of forced admissions of patients to the psychiatric hospital departments. Encompasses two seperate projects: 1. Prediciting at time of discharge for inpatient admissions. 2. Predicting day before outpatient admissions. |
| **[Coersion]**          |              | Prediction of coercion among patients admittied to the hospital psychiatric department. Encompasses predicting mechanical restraint, sedative medication and manual restraint 48 hours before coercion occurs.                        |


[Type 2 diabetes]: https://github.com/Aarhus-Psychiatry-Research/psycop-t2d
[Cancer]: https://github.com/Aarhus-Psychiatry-Research/psycop-cancer
[COPD]: https://github.com/Aarhus-Psychiatry-Research/psycop-copd
[Forced admissions]: https://github.com/Aarhus-Psychiatry-Research/psycop-forced-admissions
[Coersion]: https://github.com/Aarhus-Psychiatry-Research/pyscop-coercion

