windkit.plot.time_series.time_series

windkit.plot.time_series.time_series(ds, range_slider=True, time_range=None, mark_data_gaps=False)[source]

Create time series plot

The time series plot can be displayed for both a xarray.Dataset o xarray.DataAarray input argument. When the input is a Dataset, plots both the wind direction and wind speed time series. If the input is a DataAarray plot the its data variable. For both cases the gaps of data are identified in the time series.

Parameters:

  • ds (either a xarray.Dataset or a xarray.DataArray) –

    xarray.Dataset representing the wind direction and wind speed time series.

    xarray.DataArray representing a data variable time series.

  • range_slider (bool, optional) – Include range slider? Default: with range slider

  • time_range (list of two values [start, end] that can convert to numpy.datetime64) –

    The time series is directly shown in the defined interval.

    e.g: time_range=['2015-12-27', '2016-01-12'] will display the timeseries for this time interval.

    NOTE: all data is still plotted, only the initial view to the data is changed.

    Default shows the full data range

  • mark_data_gaps (bool, optional) –

    Mark beggining and ending of regions with data gaps in the time series?

    NOTE: Mark data gaps increases a bit the plotting time (1 to 3 sec).

    Default: without marks

Returns:

Plotly figure for display, additional modification, or output

Return type:

plotly.graph_objects.Figure