Metadata-Version: 2.1
Name: tslumen
Version: 0.0.1
Summary: A library for Time Series exploratory data analysis
Home-page: https://github.com/hsbc/tslumen
Author: HSBC
Author-email: opensource@hsbc.com
License: Apache Software License
Project-URL: Homepage, https://hsbc.github.io/tslumen
Project-URL: Repository, https://github.com/hsbc/tslumen
Project-URL: BugTracker, https://github.com/hsbc/tslumen/issues
Project-URL: Documentation, https://hsbc.github.io/tslumen/html
Project-URL: Changelog, https://github.com/hsbc/tslumen/blob/main/CHANGELOG.md
Keywords: timeseries,time-series,profiling,exploratory-data-analysis,time-series-analysis,forecasting,data-science,machine-learning,data-mining,jupyter
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: OS Independent
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Typing :: Typed
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
Provides-Extra: extras
License-File: LICENSE

![](https://raw.githubusercontent.com/hsbc/tslumen/main/doc/source/_static/logo-350.png)

## A library for exploratory analysis of Time Series data

![](https://raw.githubusercontent.com/hsbc/tslumen/main/doc/source/_static/badge_python.svg)
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**tslumen** helps bring to light the key characteristics of your time
series data with rich, pre-canned artifacts, packed with charts and
statistical information. The primary goal of tslumen is to expedite and
bring consistency to how time series EDA is performed, allowing you to
uncover the fundamental aspects in seconds rather than hours or days.

**Key features**
 * Platform agnostic, integrates nicely with your datascience workspace
 * Built on open source technology and research
 * Highly customizable and extensible
 * Data (profiling results) completely detached from the visuals
 * Can be executed from the command line
 * Efficient execution using parallel processing
 * Includes a great number of statistical information, including descriptive statistics statistical tests like KPSS or ADF, correlation, tsfeatures, etc.
 * Various plots specifically tailored to time series analysis
 * Self-contained HTML report that can easily be shared with interested parties
 * Fully interactive dashboard for a richer experience and detailed exploration

See https://hsbc.github.io/tslumen/ for the complete documentation.


## Installation

From PyPI:

```bash
pip install -U tslumen
```

From source:

```bash
# cd into tslumen after cloning the repo
make install
```


## Examples

Refer to the [Quick Start](https://hsbc.github.io/tslumen/html/quickstart.html) 
page of the documentation for a brief tour of the package.

Complete example notebooks can be found on the **User Guide** section of the documentation.


## Contributing

Contributions to tslumen are welcome. Please see our [contribution guide](CONTRIBUTING.md) for more details.




