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matplotlib.pyplot.hist2d — Matplotlib 3.1.2 documentation

matplotlib.pyplot.hist2d¶

matplotlib.pyplot.hist2d(x, y, bins=10, range=None, density=False, weights=None, cmin=None, cmax=None, *, data=None, **kwargs)[source]¶

Make a 2D histogram plot.

Parameters:

x, y : array_like, shape (n, )

Input values

bins : None or int or [int, int] or array_like or [array, array]

The bin specification:

If int, the number of bins for the two dimensions (nx=ny=bins).

If [int, int], the number of bins in each dimension (nx, ny = bins).

If array_like, the bin edges for the two dimensions (x_edges=y_edges=bins).

If [array, array], the bin edges in each dimension (x_edges, y_edges = bins).

The default value is 10.

range : array_like shape(2, 2), optional, default: None

The leftmost and rightmost edges of the bins along each dimension (if not specified explicitly in the bins parameters): [[xmin, xmax], [ymin, ymax]]. All values outside of this range will be considered outliers and not tallied in the histogram.

density : bool, optional, default: False

Normalize histogram. normed is a deprecated synonym for this parameter.

weights : array_like, shape (n, ), optional, default: None

An array of values w_i weighing each sample (x_i, y_i).

cmin : scalar, optional, default: None

All bins that has count less than cmin will not be displayed and these count values in the return value count histogram will also be set to nan upon return

cmax : scalar, optional, default: None

All bins that has count more than cmax will not be displayed (set to none before passing to imshow) and these count values in the return value count histogram will also be set to nan upon return

Returns:

h : 2D array: The bi-dimensional histogram of samples x and y. Values in x are histogrammed along the first dimension and values in y are histogrammed along the second dimension.
xedges : 1D array: The bin edges along the x axis.
yedges : 1D array: The bin edges along the y axis.
image : QuadMesh

Other Parameters:

cmap : Colormap or str, optional: A colors.Colormap instance. If not set, use rc settings.
norm : Normalize, optional: A colors.Normalize instance is used to scale luminance data to [0, 1]. If not set, defaults to colors.Normalize().
vmin/vmax : None or scalar, optional: Arguments passed to the Normalize instance.
alpha : 0 <= scalar <= 1 or None, optional: The alpha blending value.