PlotAxes.parametric(x, y, c, *, interp=0, scalex=True, scaley=True, **kwargs)[source]

Plot a parametric line.

  • *args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:

    • If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).

    • If the y coordinates are a 2D array, plot each column of data in succession (except where each column of data represents a statistical distribution, as with boxplot, violinplot, or when using means=True or medians=True).

    • If any arguments are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. A pint.Quantity embedded in an xarray.DataArray is also supported.

  • c, color, colors, values, labels (sequence of float, str, or color-spec, optional) – The parametric coordinate(s). These can be passed as a third positional argument or as a keyword argument. If they are float, the colors will be determined from norm and cmap. If they are strings, the color values will be np.arange(len(colors)) and eventual colorbar ticks will be labeled with the strings. If they are colors, they are used for the line segments and cmap is ignored – for example, colors='blue' makes a monochromatic “parametric” line.

  • interp (int, optional) – Interpolate to this many additional points between the parametric coordinates. Default is 0. This can be increased to make the color gradations between a small number of coordinates appear “smooth”.

  • data (dict-like, optional) – A dict-like dataset container (e.g., DataFrame or Dataset). If passed, each data argument can optionally be a string key and the arrays used for plotting are retrieved with data[key]. This is a native matplotlib feature.

  • autoformat (bool, optional) – Whether the x axis labels, y axis labels, axis formatters, axes titles, legend titles, and colorbar labels are automatically configured when a Series, DataFrame, DataArray, or Quantity is passed to the plotting command. Default is rc.autoformat = True. Formatting of pint.Quantity unit strings is controlled by rc.unitformat = 'L'.

Other Parameters
  • cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.

  • cmap_kw (dict-like, optional) – Passed to Colormap.

  • c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.

  • norm (norm-spec, optional) – The data value normalizer, passed to the Norm constructor function. If discrete is True then 1) this affects the default level-generation algorithm (e.g. norm='log' builds levels in log-space) and 2) this is passed to DiscreteNorm to scale the colors before they are discretized (if norm is not already a DiscreteNorm).

  • norm_kw (dict-like, optional) – Passed to Norm.

  • extend ({'neither', 'both', 'min', 'max'}, optional) – Direction for drawing colorbar “extensions” (i.e. color keys for out-of-bounds data on the end of the colorbar). Default is 'neither'.

  • discrete (bool, optional) – If False, then DiscreteNorm is not applied to the colormap. Instead, for non-contour plots, the number of levels will be roughly controlled by rc['cmap.lut']. This has a similar effect to using levels=large_number but it may improve rendering speed. Default is True for only contour-plotting commands like contourf and pseudocolor-plotting commands like pcolor.

  • sequential, diverging, cyclic, qualitative (bool, optional) – Boolean arguments used if cmap is not passed. Set these to True to use the default rc['cmap.sequential'], rc['cmap.diverging'], rc['cmap.cyclic'], and rc['cmap.qualitative'] colormaps. The diverging option also applies DivergingNorm as the default continuous normalizer.

  • vmin, vmax (float, optional) – The minimum and maximum color scale values used with the norm normalizer. If discrete is False these are the absolute limits, and if discrete is True these are the approximate limits used to automatically determine levels or values lists at “nice” intervals. If levels or values were already passed as lists, these are ignored, and vmin and vmax are set to the minimum and maximum of the lists. If robust was passed, the default vmin and vmax are some percentile range of the data values. Otherwise, the default vmin and vmax are the minimum and maximum of the data values.

  • inbounds (bool, optional) – Whether to restrict the default y (x) axis limits to account for only in-bounds data when the x (y) axis limits have been locked. Default is rc['axes.inbounds'] = True. See also rc['cmap.inbounds'].

  • scalex, scaley (bool, optional) – Whether the view limits are adapted to the data limits. The values are passed on to autoscale_view.

  • label, value (float or str, optional) – The single legend label or colorbar coordinate to be used for this plotted element. Can be numeric or string. This is generally used with 1D positional arguments.

  • colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or outer colorbar from the resulting object(s). If True, the default rc['colorbar.loc'] = 'right' is used. If the same location is used in successive plotting calls, object(s) will be added to the existing colorbar in that location (valid for colorbars built from lists of artists). Valid locations are shown in in colorbar.

  • colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.

  • legend (bool, int, or str, optional) – Location specifying where to draw an inset or outer legend from the resulting object(s). If True, the default rc['legend.loc'] = 'best' is used. If the same location is used in successive plotting calls, object(s) will be added to existing legend in that location. Valid locations are shown in legend.

  • legend_kw (dict-like, optional) – Extra keyword args for the call to legend.

  • **kwargs – Valid LineCollection properties.


LineCollection – The parametric line. See this matplotlib example.