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: