Parameters: 
 x : (n,) array or sequence of (n,) arrays
Input values, this takes either a single array or a sequence of
arrays which are not required to be of the same length.
 bins : int or sequence or str, optional
If an integer is given, bins + 1 bin edges are calculated and
returned, consistent with numpy.histogram .
If bins is a sequence, gives bin edges, including left edge of
first bin and right edge of last bin. In this case, bins is
returned unmodified.
All but the last (righthandmost) bin is halfopen. In other
words, if bins is:
then the first bin is [1, 2) (including 1, but excluding 2) and
the second [2, 3) . The last bin, however, is [3, 4] , which
includes 4.
Unequally spaced bins are supported if bins is a sequence.
With Numpy 1.11 or newer, you can alternatively provide a string
describing a binning strategy, such as 'auto', 'sturges', 'fd',
'doane', 'scott', 'rice' or 'sqrt', see
numpy.histogram .
The default is taken from rcParams["hist.bins"] .
 range : tuple or None, optional
The lower and upper range of the bins. Lower and upper outliers
are ignored. If not provided, range is (x.min(), x.max()) .
Range has no effect if bins is a sequence.
If bins is a sequence or range is specified, autoscaling
is based on the specified bin range instead of the
range of x.
Default is None
 density : bool, optional
If True , the first element of the return tuple will
be the counts normalized to form a probability density, i.e.,
the area (or integral) under the histogram will sum to 1.
This is achieved by dividing the count by the number of
observations times the bin width and not dividing by the total
number of observations. If stacked is also True , the sum of
the histograms is normalized to 1.
Default is None for both normed and density. If either is
set, then that value will be used. If neither are set, then the
args will be treated as False .
If both density and normed are set an error is raised.
 weights : (n, ) array_like or None, optional
An array of weights, of the same shape as x. Each value in x
only contributes its associated weight towards the bin count
(instead of 1). If normed or density is True ,
the weights are normalized, so that the integral of the density
over the range remains 1.
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
counts in that bin plus all bins for smaller values. The last bin
gives the total number of datapoints. If normed or density
is also True then the histogram is normalized such that the
last bin equals 1. If cumulative evaluates to less than 0
(e.g., 1), the direction of accumulation is reversed.
In this case, if normed and/or density is also True , then
the histogram is normalized such that the first bin equals 1.
Default is False
 bottom : array_like, scalar, or None
Location of the bottom baseline of each bin. If a scalar,
the base line for each bin is shifted by the same amount.
If an array, each bin is shifted independently and the length
of bottom must match the number of bins. If None, defaults to 0.
Default is None
 histtype : {'bar', 'barstacked', 'step', 'stepfilled'}, optional
The type of histogram to draw.
 'bar' is a traditional bartype histogram. If multiple data
are given the bars are arranged side by side.
 'barstacked' is a bartype histogram where multiple
data are stacked on top of each other.
 'step' generates a lineplot that is by default
unfilled.
 'stepfilled' generates a lineplot that is by default
filled.
Default is 'bar'
 align : {'left', 'mid', 'right'}, optional
Controls how the histogram is plotted.
 'left': bars are centered on the left bin edges.
 'mid': bars are centered between the bin edges.
 'right': bars are centered on the right bin edges.
Default is 'mid'
 orientation : {'horizontal', 'vertical'}, optional
If 'horizontal', barh will be used for
bartype histograms and the bottom kwarg will be the left edges.
 rwidth : scalar or None, optional
The relative width of the bars as a fraction of the bin width. If
None , automatically compute the width.
Ignored if histtype is 'step' or 'stepfilled'.
Default is None
 log : bool, optional
If True , the histogram axis will be set to a log scale. If
log is True and x is a 1D array, empty bins will be
filtered out and only the nonempty (n, bins, patches)
will be returned.
Default is False
 color : color or array_like of colors or None, optional
Color spec or sequence of color specs, one per dataset. Default
(None ) uses the standard line color sequence.
Default is None
 label : str or None, optional
String, or sequence of strings to match multiple datasets. Bar
charts yield multiple patches per dataset, but only the first gets
the label, so that the legend command will work as expected.
default is None
 stacked : bool, optional
If True , multiple data are stacked on top of each other If
False multiple data are arranged side by side if histtype is
'bar' or on top of each other if histtype is 'step'
Default is False
 normed : bool, optional
Deprecated; use the density keyword argument instead.
