darray ( DataArray ) – Must be two-dimensional, unless creating faceted plots.

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

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

figsize ( Iterable or 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.

ax ( matplotlib axes object , optional ) – Axes on which to plot. By default, use the current axes. Mutually exclusive with size and figsize .

row ( Hashable or None , optional ) – If passed, make row faceted plots on this dimension name.

col ( Hashable or None , optional ) – If passed, make column faceted plots on this dimension name.

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

xincrease ( None , True , or False , optional ) – Should the values on the x axis be increasing from left to right? If None , use the default for the Matplotlib function.

yincrease ( None , True , or False , optional ) – Should the values on the y axis be increasing from top to bottom? If None , use the default for the Matplotlib function.

add_colorbar ( bool , optional ) – Add colorbar to axes.

add_labels ( bool , optional ) – Use xarray metadata to label axes.

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.

cmap ( matplotlib colormap name or colormap , optional ) – The mapping from data values to color space. If not provided, this will be either be '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 and the plot type is not 'contour' or 'contourf' , levels must also be specified.

center ( float or False , 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) .

infer_intervals ( bool , optional ) – Only applies to pcolormesh. If True , the coordinate intervals are passed to pcolormesh. If False , the original coordinates are used (this can be useful for certain map projections). The default is to always infer intervals, unless the mesh is irregular and plotted on a map projection.

colors ( str or array-like of color-like , optional ) – A single color or a sequence of colors. If the plot type is not 'contour' or 'contourf' , the levels argument is required.

subplot_kws ( dict , optional ) – Dictionary of keyword arguments for Matplotlib subplots. Only used for 2D and faceted plots. (see matplotlib.figure.Figure.add_subplot() ).

cbar_ax ( matplotlib axes object , optional ) – Axes in which to draw the colorbar.

cbar_kwargs ( dict , optional ) – Dictionary of keyword arguments to pass to the colorbar (see matplotlib.figure.Figure.colorbar() ).

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.

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

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