xarray.plot.scatter#

xarray.plot.scatter(ds, x, y, ax, **kwargs)[source]#

Scatter Dataset data variables against each other.

Wraps matplotlib.pyplot.scatter().

Parameters

  • ds (Dataset)

  • x, y (str) – Variable names for the x and y grid positions.

  • u, v (str, optional) – Variable names for the u and v velocities (in x and y direction, respectively; quiver/streamplot plots only).

  • hue (str, optional) – Variable by which to color scatter points or arrows.

  • hue_style ({'continuous', 'discrete'}, optional) – How to use the hue variable:

    • 'continuous' – continuous color scale (default for numeric hue variables)

    • 'discrete' – a color for each unique value, using the default color cycle (default for non-numeric hue variables)

  • markersize (str, optional) – Variable by which to vary the size of scattered points (scatter plot only).

  • size_norm (matplotlib.colors.Normalize or tuple, optional) – Used to normalize the markersize variable. If a tuple is passed, the values will be passed to matplotlib.colors.Normalize as arguments. Default: no normalization (vmin=None, vmax=None, clip=False).

  • scale (scalar, optional) – Quiver only. Number of data units per arrow length unit. Use this to control the length of the arrows: larger values lead to smaller arrows.

  • add_guide (bool, optional, default: True) – Add a guide that depends on hue_style:

    • 'continuous' – build a colorbar

    • 'discrete' – build a legend

  • row (str, optional) – If passed, make row faceted plots on this dimension name.

  • col (str, optional) – If passed, make column faceted plots on this dimension name.

  • col_wrap (int, optional) – Use together with col to wrap faceted plots.

  • ax (matplotlib axes object, optional) – If None, use the current axes. Not applicable when using facets.

  • subplot_kws (dict, optional) – Dictionary of keyword arguments for Matplotlib subplots (see matplotlib.figure.Figure.add_subplot()). Only applies to FacetGrid plotting.

  • aspect (scalar, optional) – Aspect ratio of plot, so that aspect * size gives the width in inches. Only used if a size is provided.

  • size (scalar, optional) – If provided, create a new figure for the plot with the given size: height (in inches) of each plot. See also: aspect.

  • norm (matplotlib.colors.Normalize, optional) – If norm has vmin or vmax specified, the corresponding kwarg must be None.

  • vmin, vmax (float, optional) – Values to anchor the colormap, otherwise they are inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting one of these values will fix the other by symmetry around center. Setting both values prevents use of a diverging colormap. If discrete levels are provided as an explicit list, both of these values are ignored.

  • cmap (matplotlib colormap name or colormap, optional) – The mapping from data values to color space. Either a Matplotlib colormap name or object. If not provided, this will be either 'viridis' (if the function infers a sequential dataset) or 'RdBu_r' (if the function infers a diverging dataset). See Choosing Colormaps in Matplotlib for more information.

    If seaborn is installed, cmap may also be a seaborn color palette. Note: if cmap is a seaborn color palette, levels must also be specified.

  • colors (str or array-like of color-like, optional) – A single color or a list of colors. The levels argument is required.

  • center (float, optional) – The value at which to center the colormap. Passing this value implies use of a diverging colormap. Setting it to False prevents use of a diverging colormap.

  • robust (bool, optional) – If True and vmin or vmax are absent, the colormap range is computed with 2nd and 98th percentiles instead of the extreme values.

  • extend ({'neither', 'both', 'min', 'max'}, optional) – How to draw arrows extending the colorbar beyond its limits. If not provided, extend is inferred from vmin, vmax and the data limits.

  • levels (int or array-like, optional) – Split the colormap (cmap) into discrete color intervals. If an integer is provided, “nice” levels are chosen based on the data range: this can imply that the final number of levels is not exactly the expected one. Setting vmin and/or vmax with levels=N is equivalent to setting levels=np.linspace(vmin, vmax, N).

  • **kwargs (optional) – Additional keyword arguments to wrapped Matplotlib function.