NOAAPredictIndicesTimeSeries

class sunpy.timeseries.sources.NOAAPredictIndicesTimeSeries(data, meta=None, units=None, **kwargs)[source]

Bases: GenericTimeSeries

NOAA Solar Cycle Predicted Progression.

The predictions are updated monthly and are produced by ISES. Observed values are initially the preliminary values which are replaced with the final values as they become available.

The following predicted values are available.

Note

See the gallery example Plotting a solar cycle index for how to use Fido to retrieve the data file.

Examples

>>> import sunpy.timeseries
>>> noaa_url = 'https://services.swpc.noaa.gov/json/solar-cycle/predicted-solar-cycle.json'  
>>> noaa = sunpy.timeseries.TimeSeries(noaa_url, source='NOAAPredictIndices')  
>>> noaa.peek()  

References

Methods Summary

is_datasource_for(**kwargs)

Determines if header corresponds to an NOAA predict indices TimeSeries.

plot([axes, columns])

Plots predicted NOAA Indices as a function of time from a pandas dataframe.

Methods Documentation

classmethod is_datasource_for(**kwargs)[source]

Determines if header corresponds to an NOAA predict indices TimeSeries.

plot(axes=None, columns=None, **plot_args)[source]

Plots predicted NOAA Indices as a function of time from a pandas dataframe.

Parameters:
  • axes (matplotlib.axes.Axes, optional) – The axes on which to plot the TimeSeries.

  • columns (list[str], optional) – Unused, but there to maintain uniformity among plot methods.

  • **kwargs (dict) – Additional plot keyword arguments that are handed to plot functions.

Returns:

Axes – The plot axes.