, alpha=0.5, bins=50, color=None, colors=None, labels=None, hist=None, kde=None, bw_method=None, xlabel=None, ylabel=None, xlim=None, ylim=None, cutoff=None, xscale=None, yscale=None, xticks=None, yticks=None, fontsize=None, legend_fontsize=None, figsize=None, normed=None, perc=None, exclude_zeros=None, axvline=None, axhline=None, pdf=None, ax=None, dpi=None, show=True, **kwargs)

Plot a histogram.

arrays : : list or array (default [‘royalblue’, ‘white’, ‘forestgreen’])

List of colors, either as names or rgb values.

alpha : list, np.ndarray or None (default: None)

Alpha of the colors. Must be same length as colors.

bins : int or sequence (default: 50)

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.

colors : : list or array (default [‘royalblue’, ‘white’, ‘forestgreen’])

List of colors, either as names or rgb values.

labels : str or None (default: None)

String, or sequence of strings to label clusters.

hist : bool or None (default: None)

Whether to show histogram.

kde : bool or None (default: None)

Whether to use kernel density estimation on data.

bw_method : str, scalar or callable, (default: None)

The method used to calculate the estimator bandwidth. This can be ‘scott’, ‘silverman’, a scalar constant or a callable. If a scalar, this will be used directly as kde.factor. If a callable, it should take a gaussian_kde instance as only parameter and return a scalar. If None (default), nothing happens; the current kde.covariance_factor method is kept.

xlabel : str (default: None)

Label of x-axis.

ylabel : str (default: None)

Label of y-axis.

xlim : tuple, e.g. [0,1] or None (default: None)

Restrict x-limits of the axis.

ylim : tuple, e.g. [0,1] or None (default: None)

Restrict y-limits of the axis.

cutoff : tuple, e.g. [0,1] or float or None (default: None)

Bins will be cut off below and above the cutoff values.

xscale : log or None (default: None)

Scale of the x-axis.

yscale : log or None (default: None)

Scale of the y-axis.

fontsize : float (default: None)

Label font size.

legend_fontsize : int (default: None)

Legend font size.

figsize : tuple (default: (7,5))

Figure size.

normed : bool or None (default: None)

Whether to normalize data.

perc : tuple, e.g. [2,98] (default: None)

Specify percentile for continuous coloring.

exclude_zeros : bool or None (default: None)

Whether to exclude zeros in data for the kde and hist plot.

axvline : float or None (default: None)

Plot a vertical line at the specified x-value.

float or None (default : axhline

Plot a horizontal line at the specified y-value.

pdf : str or None (default: None)

probability density function to be fitted, e.g., ‘norm’, ‘t’, ‘chi’, ‘beta’, ‘gamma’, ‘laplace’ etc.

ax : matplotlib.Axes, optional (default: None)

A matplotlib axes object. Only works if plotting a single component.

dpi : int (default: 80)

Figure dpi.

show : bool, optional (default: None)

Show the plot, do not return axis.


If show==False a matplotlib.Axis