phenodata is a data acquisition and manipulation toolkit for open access phenology data
Project description
phenodata - phenology data acquisition for humans
About
phenodata is a data acquisition and manipulation toolkit for open access phenology data. It is written in Python.
Currently, it implements data wrappers for acquiring phenology observation data published on the DWD Climate Data Center (CDC) FTP server operated by »Deutscher Wetterdienst« (DWD).
Under the hood, it uses the fine Pandas data analysis library for data mangling, amongst others.
Acknowledgments
Thanks to the many observers, »Deutscher Wetterdienst«, the »Global Phenological Monitoring programme« and all people working behind the scenes for their commitment in recording the observations and for making the excellent datasets available to the community. You know who you are.
Getting started
Install
If you know your way around Python, installing this software is really easy:
pip install phenodata --upgrade
Please refer to the virtualenv page about further guidelines how to install and use this software.
Usage
Display list of species:
phenodata list-species --source=dwd
Display list of phases:
phenodata list-phases --source=dwd
Display list of stations:
phenodata list-stations --source=dwd --dataset=immediate
Display “beginning of flowering” events for hazel and snowdrop around Berlin and Brandenburg (Germany) in 2017:
phenodata tabular --source=dwd --dataset=immediate --year=2017 --regions=berlin,brandenburg --species=hasel,schneeglöckchen --bbch=60
Display forecast for “beginning of flowering” events for canola and sweet cherry around Thüringen and Bayern (Germany) in 2017:
phenodata tabular --source=dwd --dataset=immediate --forecast --regions=thüringen,bayern --species=raps,süßkirsche --bbch=60
You can choose between two different datasets, annual-reporters and immediate-reporters.
Project information
The “phenodata” program is released under the AGPL license. The code lives on GitHub and the Python package is published to PyPI. You might also want to have a look at the documentation.
The software has been tested on Python 2.7.
If you’d like to contribute you’re most welcome! Spend some time taking a look around, locate a bug, design issue or spelling mistake and then send us a pull request or create an issue.
Thanks in advance for your efforts, we really appreciate any help or feedback.
Disclaimer
The project and its authors are not affiliated with DWD, USA-NPN or any other data provider in any way. It is a sole project from the community for making data more accessible in the spirit of open data.
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