ruins.plotting.climate_parcoords#

Module Contents#

Functions#

climate_projection_parcoords(data[, fig, align_range, ...])

Parallel coordinates plot for climate projections.

Attributes#

DIMENSIONS

ruins.plotting.climate_parcoords.DIMENSIONS#
ruins.plotting.climate_parcoords.climate_projection_parcoords(data: pandas.DataFrame, fig: plotly.graph_objects.Figure = None, align_range: bool = True, colorscale='electric', row: int = 1, col: int = 1, lang='en')#

Parallel coordinates plot for climate projections. This plot uses each month in the year as a coordinate dimension. By sorting the dimensions into the correct order, the cycle of annual temperature aggregates is preserved, while the full dataset can easily be compared.

Parameters:

  • data (pandas.DataFrame) – Dataframe with the data to plot. The DataFrame has to be indexed by a Datetime Index and does accept more than one column (ground station, RCP scenario or grid cell).

  • fig (plotly.graph_objects.Figure) – If not None, the given figure will be used to plot the data. Note, that subfigures need to use the 'domain' type.

  • align_range (bool) – If True (default) each dimension (aka month) will use the same value range, to focus the differences between the months. If False, the range will be adapted to span from min to max for each dimension, putting more focus on the differences between the years (decades).

  • colorscale (str) – Name identifier of teh colorscale. See plotly to learn about available options.

  • row (int) – If figure is not None, row and column can be used to plot into the correct subplot.

  • col (int) – If figure is not None, row and column can be used to plot into the correct subplot.

  • lang (str) – Can either be 'en' or 'de'. As of now, the language does not have any effect.