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Feb 23, 2019
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Document histogramming pre-binned data. #13459

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20 changes: 15 additions & 5 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -6410,10 +6410,11 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
"""
Plot a histogram.

Compute and draw the histogram of *x*. The return value is a
tuple (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*,
[*patches0*, *patches1*,...]) if the input contains multiple
data.
Compute and draw the histogram of *x*. The return value is a tuple
(*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*, [*patches0*,
*patches1*,...]) if the input contains multiple data. See the
documentation of the *weights* parameter to draw a histogram of
already-binned data.

Multiple data can be provided via *x* as a list of datasets
of potentially different length ([*x0*, *x1*, ...]), or as
Expand Down Expand Up @@ -6487,7 +6488,16 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
the weights are normalized, so that the integral of the density
over the range remains 1.

Default is ``None``
Default is ``None``.

This parameter can be used to draw a histogram of data that has
already been binned, e.g. using `np.histogram` (by treating each
bin as a single point with a weight equal to its count) ::

counts, bins = np.histogram(data)
plt.hist(bins[:-1], bins, weights=counts)

(or you may alternatively use `~.bar()`).

cumulative : bool, optional
If ``True``, then a histogram is computed where each bin gives the
Expand Down