Class Bins

bqplot/marks.py:1158–1257

Backend histogram mark. A `Bars` instance that bins sample data. It is very similar in purpose to the `Hist` mark, the difference being that the binning is done in the backend (python), which avoids large amounts of data being shipped back and forth to the frontend. It should there

@register_mark('bqplot.Bins')
class Bins(Bars):

    """Backend histogram mark.

    A `Bars` instance that bins sample data.

    It is very similar in purpose to the `Hist` mark, the difference being that
    the binning is done in the backend (python), which avoids large amounts of
    data being shipped back and forth to the frontend. It should therefore be
    preferred for large data.
    The binning method is the numpy `histogram` method.

    The following  documentation is in part taken from the numpy documentation.

    Data Attributes
    ---------------

    Attributes
    ----------
    sample: numpy.ndarray (default: [])
        sample of which the histogram must be computed.

    Style Attributes
    ----------------

    Attributes
    ----------
    icon: string (class-level attribute)
        font-awesome icon for that mark
    name: string (class-level attribute)
        user-friendly name of the mark
    bins: nonnegative int (default: 10)
          or {'auto', 'fd', 'doane', 'scott', 'rice', 'sturges', 'sqrt'}
        If `bins` is an int, it defines the number of equal-width
        bins in the given range (10, by default).
        If `bins` is a string (method name), `histogram` will use
        the method chosen to calculate the optimal bin width and
        consequently the number of bins (see `Notes` for more detail on
        the estimators) from the data that falls within the requested
        range.
    density : bool (default: `False`)
        If `False`, the height of each bin is the number of samples in it.
        If `True`, the height of each bin is the value of the
        probability *density* function at the bin, normalized such that
        the *integral* over the range is 1. Note that the sum of the
        histogram values will not be equal to 1 unless bins of unity
        width are chosen; it is not a probability *mass* function.
    min : float (default: None)
        The lower range of the bins.  If not provided, lower range
        is simply `x.min()`.
    max : float (default: None)
        The upper range of the bins.  If not provided, lower range
        is simply `x.max()`.

    !!! Note
        - The fields which can be passed to the default tooltip are:
            - All the `Bars` data attributes (`x`, `y`, `color`)
            - **index**: index of the bin