We encourage you to follow our code of conduct. If you are using Python Windrose and want to interact with developers, others users. Install latest development version $ pip install git+įull documentation of library is available at Community guidelines click (for command line interface tools)Ī package is available and can be downloaded from PyPi and installed using: $ pip install windrose.Scipy (to fit data with Weibull distribution).Pandas (to feed plot functions easily).They are using it to visualize the motion of storms based on the relative position of the lightning from one strike to the next. Some academics use it to track lightning strikes during high intensity storms. Some others contributors have used it to make figures for a wind power plant control optimization study. It is also used by some contributors for teaching purpose. Data from local pollution measures and meteorologic information from various sources like Meteo-France were used to generate a pollution source wind rose. The initial use case of this library was for a technical report concerning pollution exposure and wind distributions analyzes. Windrose is a Python library to manage wind data, draw windroses (also known as polar rose plots), and fit Weibull probability density functions. Data can be passed to the package using Numpy arrays or a Pandas DataFrame. The wind rose tool uses Matplotlib as a backend. It can also be used to describe air quality pollution sources. A wind rose is a graphic tool used by meteorologists to give a succinct view of how wind speed and direction are typically distributed at a particular location.
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