@@ -6410,10 +6410,11 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
64106410 """
64116411 Plot a histogram.
64126412
6413- Compute and draw the histogram of *x*. The return value is a
6414- tuple (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*,
6415- [*patches0*, *patches1*,...]) if the input contains multiple
6416- data.
6413+ Compute and draw the histogram of *x*. The return value is a tuple
6414+ (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*, [*patches0*,
6415+ *patches1*,...]) if the input contains multiple data. See the
6416+ documentation of the *weights* parameter to draw a histogram of
6417+ already-binned data.
64176418
64186419 Multiple data can be provided via *x* as a list of datasets
64196420 of potentially different length ([*x0*, *x1*, ...]), or as
@@ -6487,7 +6488,16 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
64876488 the weights are normalized, so that the integral of the density
64886489 over the range remains 1.
64896490
6490- Default is ``None``
6491+ Default is ``None``.
6492+
6493+ This parameter can be used to draw a histogram of data that has
6494+ already been binned, e.g. using `np.histogram` (by treating each
6495+ bin as a single point with a weight equal to its count) ::
6496+
6497+ counts, bins = np.histogram(data)
6498+ plt.hist(bins[:-1], bins, weights=counts)
6499+
6500+ (or you may alternatively use `~.bar()`).
64916501
64926502 cumulative : bool, optional
64936503 If ``True``, then a histogram is computed where each bin gives the
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