xarray.Dataset.plot.scatter

xarray.Dataset.plot.scatter#

Dataset.plot.scatter(*args, x=None, y=None, z=None, hue=None, hue_style=None, markersize=None, linewidth=None, figsize=None, size=None, aspect=None, ax=None, row=None, col=None, col_wrap=None, xincrease=True, yincrease=True, add_legend=None, add_colorbar=None, add_labels=True, add_title=True, subplot_kws=None, xscale=None, yscale=None, xticks=None, yticks=None, xlim=None, ylim=None, cmap=None, vmin=None, vmax=None, norm=None, extend=None, levels=None, **kwargs)[source]#

Scatter variables against each other.

Wraps matplotlib.pyplot.scatter().

The y DataArray will be used as base, any other variables are added as coords.

Parameters:

  • ds (Dataset) – Must be 2 dimensional, unless creating faceted plots.

  • x (Hashable or None, optional) – Coordinate for x axis. If None use ds.dims[1].

  • y (Hashable or None, optional) – Coordinate for y axis. If None use ds.dims[0].

  • z (Hashable or None, optional) – If specified plot 3D and use this coordinate for z axis.

  • hue (Hashable or None, optional) – Dimension or coordinate for which you want multiple lines plotted.

  • markersize (Hashable or None, optional) – scatter only. Variable by which to vary size of scattered points.

  • linewidth (Hashable or None, optional) – Variable by which to vary linewidth.

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

  • col (Hashable, 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, uses the current axis. Not applicable when using facets.

  • figsize (Iterable[float] or None, optional) – A tuple (width, height) of the figure in inches. Mutually exclusive with size and ax.

  • 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.

  • aspect ("auto", "equal", scalar or None, optional) – Aspect ratio of plot, so that aspect * size gives the width in inches. Only used if a size is provided.

  • xincrease (bool or None, default: True) – Should the values on the x axes be increasing from left to right? if None, use the default for the matplotlib function.

  • yincrease (bool or None, default: True) – Should the values on the y axes be increasing from top to bottom? if None, use the default for the matplotlib function.

  • add_legend (bool or None, optional) – If True use xarray metadata to add a legend.

  • add_colorbar (bool or None, optional) – If True add a colorbar.

  • add_labels (bool or None, optional) – If True use xarray metadata to label axes

  • add_title (bool or None, optional) – If True use xarray metadata to add a title

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

  • xscale ({'linear', 'symlog', 'log', 'logit'} or None, optional) – Specifies scaling for the x-axes.

  • yscale ({'linear', 'symlog', 'log', 'logit'} or None, optional) – Specifies scaling for the y-axes.

  • xticks (ArrayLike or None, optional) – Specify tick locations for x-axes.

  • yticks (ArrayLike or None, optional) – Specify tick locations for y-axes.

  • xlim (tuple[float, float] or None, optional) – Specify x-axes limits.

  • ylim (tuple[float, float] or None, optional) – Specify y-axes limits.

  • 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.

  • vmin (float or None, optional) – Lower value to anchor the colormap, otherwise it is inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting vmin or vmax 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.

  • vmax (float or None, optional) – Upper value to anchor the colormap, otherwise it is inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting vmin or vmax 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.

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

  • 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 arguments to wrapped matplotlib function

Returns:

artist – The same type of primitive artist that the wrapped matplotlib function returns