PlotAxes.hexbin¶

PlotAxes.hexbin(x, y, weights, **kwargs)[source]¶

Plot a 2D hexagonally binned histogram.

Parameters

*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.
weights (array-like, optional) – The weights associated with each point. If string this can be retrieved from data (see below).
data (dict-like, optional) – A dict-like dataset container (e.g., DataFrame or DataArray). If passed, positional arguments can optionally be string data keys 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.

Other Parameters

cmap (colormap spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
norm (normalizer spec, optional) – The continuous colormap normalizer, passed to the Norm constructor function. If discrete is True this is also used to normalize values passed to DiscreteNorm before colors is selected.
norm_kw (dict-like, optional) – Passed to Norm.
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 False for imshow, matshow, spy, hexbin, hist2d, and heatmap plots, but True otherwise.
sequential (bool, optional) – Use rc['cmap.sequential'] = 'fire' as the default colormap.
diverging (bool, optional) – Use rc['cmap.diverging'] = 'negpos' as the default colormap and use DivergingNorm as the default continuous normalizer. This will also ensure auto-generated levels include a value at zero.
cyclic (bool, optional) – Use rc['cmap.cyclic'] = 'twilight' as the default colormap and modify the default arguments passed to DiscreteNorm so that colors on either end are distinct.
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 latter three options also change level- and norm-generation behavior.
extend ({{'neither', 'min', 'max', 'both'}}, optional) – Whether to assign unique colors to out-of-bounds data and draw colorbar “extensions” when a colorbar is drawn.
N – Shorthand for levels.
levels (int or list of float, optional) – The number of level edges or a list of level edges. If the former, locator is used to generate this many level edges at “nice” intervals. If the latter, the levels should be monotonically increasing or decreasing (note that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or list of float, optional) – The number of level centers or a list of level centers. If the former, locator is used to generate this many level centers at “nice” intervals. If the latter, levels are inferred using edges. This will override any levels input.
vmin, vmax (float, optional) – Used to determine level locations if levels or values is an integer. Actual levels may not fall exactly on vmin and vmax, but the minimum level will be no smaller than vmin and the maximum level will be no larger than vmax. If vmin or vmax are not provided, the minimum and maximum data values are used.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or panel colorbar from the resulting object(s). If True, the default rc['colorbar.loc'] = 'right' is used. Valid locations are described in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or panel legend from the resulting object(s). If True, the default rc['legend.loc'] = 'best' is used. Valid locations are described in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to hexbin.