Method hist

hvplot/plotting/core.py:1026–1105

A `histogram` displays an approximate representation of the distribution of continuous data. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.hist.html Plotting options: https://hvplot.holoviz.org/ref/plotting_options/index.html Parameters

(
        self, y=None, by=None, bins=20, bin_range=None, normed=False, cumulative=False, **kwds
    )

        return self(kind='violin', x=None, y=y, by=by, **dict(kwds, hover=False))

    def hist(
        self, y=None, by=None, bins=20, bin_range=None, normed=False, cumulative=False, **kwds
    ):
        """
        A `histogram` displays an approximate representation of the distribution of continuous data.

        Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.hist.html

        Plotting options: https://hvplot.holoviz.org/ref/plotting_options/index.html

        Parameters
        ----------
        y : string or sequence
            Field(s) in the *wide* data to compute the distribution(s) from.
            Please note the fields should contain continuous data. Not categorical.
        by : string or sequence
            Field(s) in the *long* data to group by.
        bins : int or string or np.ndarray or list or tuple, optional
            The number of bins in the histogram, or an explicit set of bin edges
            or a method to find the optimal set of bin edges, e.g. 'auto', 'fd',
            'scott' etc. For more documentation on these approaches see the
            :func:`numpy.histogram_bin_edges` documentation. Default is 20.
        bin_range: tuple, optional
            The lower and upper range of the bins.
            Default is the minimum and maximum values of the continuous data.
        normed : str or bool, optional
            Controls normalization behavior.  If ``True`` or ``'integral'``, then
            ``density=True`` is passed to np.histogram, and the distribution
            is normalized such that the integral is unity.  If ``False``,
            then the frequencies will be raw counts. If ``'height'``, then the
            frequencies are normalized such that the max bin height is unity.
            Default is False.
        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 data points. Default is False.
        kwds : optional
            Additional keywords arguments are documented in :ref:`plot-options`.
            Run ``hvplot.help('hist')`` for the full method documentation.

        Returns
        -------
        :class:`holoviews:holoviews.element.Histogram` / Panel object
            You can `print` the object to study its composition and run:

            .. code-block::

                import holoviews as hv
                hv.help(the_holoviews_object)

            to learn more about its parameters and options.

        See Also
        --------
        kde : Kernel Density Estimate plot.
        bivariate : 2D KDE plot.
        contour : Isolines plot for gridded data.