# xarray.plot.pcolormesh

`xarray.plot.``pcolormesh`(x, y, z, ax, infer_intervals=None, **kwargs)

  Pseudocolor plot of 2d DataArray

  Wraps `matplotlib:matplotlib.pyplot.pcolormesh()`

  Parameters:

  darray : DataArray

  > Must be 2 dimensional, unless creating faceted plots

  x : string, optional

  > Coordinate for x axis. If None use darray.dims[1]

  y : string, optional

  > Coordinate for y axis. If None use darray.dims[0]

  figsize : tuple, optional

  > A tuple (width, height) of the figure in inches. Mutually exclusive with `size` and `ax`.

  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`.

  ax : matplotlib axes object, optional

  > Axis on which to plot this figure. By default, use the current axis. Mutually exclusive with `size` and `figsize`.

  row : string, optional

  > If passed, make row faceted plots on this dimension name

  col : string, optional

  > If passed, make column faceted plots on this dimension name

  col_wrap : integer, optional

  > Use together with `col` to wrap faceted plots

  xincrease : None, True, or False, optional

  > Should the values on the x axes 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 axes be increasing from top to bottom? if None, use the default for the matplotlib function

  add_colorbar : Boolean, optional

  > Adds colorbar to axis

  add_labels : Boolean, optional

  > Use xarray metadata to label axes

  vmin, vmax : floats, 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 object, 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). When Seaborn is installed, `cmap` may also be a seaborn color palette. If `cmap` is seaborn color palette and the plot type is not `contour` or `contourf`, `levels` must also be specified.

  colors : discrete colors to plot, optional

  > A single color or a list of colors. If the plot type is not `contour` or `contourf`, 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 list-like object, 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.

  subplot_kws : dict, optional

  > Dictionary of keyword arguments for matplotlib subplots. Only applies to FacetGrid plotting.

  cbar_ax : matplotlib Axes, optional

  > Axes in which to draw the colorbar.

  cbar_kwargs : dict, optional

  > Dictionary of keyword arguments to pass to the colorbar.

  **kwargs : optional

  > Additional arguments to wrapped matplotlib function

  Returns:

  artist :

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