atmospy.pollutionroseplot

atmospy.pollutionroseplot(data=None, *, ws=None, wd=None, pollutant=None, faceted=False, segments=12, bins=[0, 10, 100, 1000, inf], suffix='a.u.', calm=0.0, lw=1, legend=True, palette='flare', title=None, **kwargs)

Plot the intensity and directionality of a variable on a traditional wind-rose plot.

This function is a modified version of Phil Hobson’s work.

Traditionally, a wind rose plots wind speed and direction so that you can see from what direction is the wind coming from and at what velocity. For air quality purposes, we often wonder whether or not there is directionality to the intensity of a certain air pollutant. Well, look no further. This plot allows you to easily visualize the directionality of a pollutant.

Parameters:

datapandas.DataFrame

Tabular data as a pandas DataFrame.

wskey in data

Variable that corresponds to the wind speed data in data.

wdkey in data

Variable that corresponds to the wind direction data in data.

pollutantkey in data

Variable that corresponds to the pollutant of interest in data.

facetedbool, optional

Set to True if plotting on a FacetGrid, by default False

segmentsint, optional

The number of bins along the theta axis to group by wind direction , by default 12

binslist or array of floats, optional

An array of floats corresponding to the bin boundaries for pollutant; if the last entry is not inf, it will be automatically added, by default [0, 10, 100, 1000]

suffixstr, optional

The suffix (or units) to use on the labels for pollutant, by default “a.u.”

calmfloat, optional

Set the definition of calm conditions; data under calm winds will not be used to compute the statistics and will be shown on the plot as blank in the center, by default 0.

lwint, optional

Set the line width, by default 1

legendbool, optional

If True a legend will be added to the figure, by default True

palettestr, optional

Select the color palette to use, by default “flare”

titlestr, optional

Set the figure title, by default None

Returns:

matplotlib.axes._axes.Axes

Examples

Using defaults, plot the pollution rose for PM2.5:

>>> df = atmospy.load_dataset("air-sensors-met")
>>> atmospy.pollutionroseplot(data=df, ws="ws", wd="wd", pollutant="pm25")