A package for converting time series data from e.g. electronic health records into wide format data.
Project description
Time-series Flattener
Roadmap
Roadmap is tracked on our kanban board.
🔧 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 |
💬 Where to ask questions
Type | |
---|---|
🚨 Bug Reports | GitHub Issue Tracker |
🎁 Feature Requests & Ideas | GitHub Issue Tracker |
👩💻 Usage Questions | GitHub Discussions |
🗯 General Discussion | GitHub 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. |
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
timeseriesflattener-0.13.0.tar.gz
(20.5 kB
view hashes)
Built Distribution
Close
Hashes for timeseriesflattener-0.13.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | e8ac4868977710a1a13ae2f85ca9cb45736549548b6c014b75a3a638b4a37a7f |
|
MD5 | 879cf6810823c97864351f2731c9eb05 |
|
BLAKE2b-256 | 2dc8a6fbd331ef14f75c9d966c002066fe8175064376ebbdf0055b50f8be4a91 |
Close
Hashes for timeseriesflattener-0.13.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ffcee5062e45e962a34ffa4bb7c4b97c7a65e37c030e0848c6a4e89b132e47e7 |
|
MD5 | dff6e3bbc957450507a5bf505bd2cf63 |
|
BLAKE2b-256 | db7cb19aed0c70a813cf6e78d940a01377c949878eaf7b627036d9a915f25019 |