packages/vaex-core/vaex/dataframe.py
def plot_widget(self, x, y, z=None, grid=None, shape=256, limits=None, what="count(*)", figsize=None,
                    f="identity", figure_key=None, fig=None, axes=None, xlabel=None, ylabel=None, title=None,
                    show=True, selection=[None, True], colormap="afmhot", grid_limits=None, normalize="normalize",
                    grid_before=None,
                    what_kwargs={}, type="default",
                    scales=None, tool_select=False, bq_cleanup=True,
                    backend="bqplot",
                    **kwargs):
        """Viz 1d, 2d or 3d in a Jupyter notebook

        .. note::
            This API is not fully settled and may change in the future

        Example:

        >>> df.plot_widget(df.x, df.y, backend='bqplot')
        >>> df.plot_widget(df.pickup_longitude, df.pickup_latitude, backend='ipyleaflet')

        :param backend: Widget backend to use: 'bqplot', 'ipyleaflet', 'ipyvolume', 'matplotlib'

        """
        import vaex.jupyter.plot
        backend = vaex.jupyter.plot.create_backend(backend)
        cls = vaex.jupyter.plot.get_type(type)
        x = _ensure_strings_from_expressions(x)
        y = _ensure_strings_from_expressions(y)
        z = _ensure_strings_from_expressions(z)
        for name in 'vx vy vz'.split():
            if name in kwargs:
                kwargs[name] = _ensure_strings_from_expressions(kwargs[name])
        plot2d = cls(backend=backend, dataset=self, x=x, y=y, z=z, grid=grid, shape=shape, limits=limits, what=what,
                     f=f, figure_key=figure_key, fig=fig,
                     selection=selection, grid_before=grid_before,
                     grid_limits=grid_limits, normalize=normalize, colormap=colormap, what_kwargs=what_kwargs, **kwargs)
        if show:
            plot2d.show()
        return plot2d
def plot_widget(self, x, y, z=None, grid=None, shape=256, limits=None, what="count(*)", figsize=None,
                    f="identity", figure_key=None, fig=None, axes=None, xlabel=None, ylabel=None, title=None,
                    show=True, selection=[None, True], colormap="afmhot", grid_limits=None, normalize="normalize",
                    grid_before=None,
                    what_kwargs={}, type="default",
                    scales=None, tool_select=False, bq_cleanup=True,
                    backend="bqplot",
                    **kwargs):
        """Viz 1d, 2d or 3d in a Jupyter notebook

        .. note::
            This API is not fully settled and may change in the future

        Example:

        >>> df.plot_widget(df.x, df.y, backend='bqplot')
        >>> df.plot_widget(df.pickup_longitude, df.pickup_latitude, backend='ipyleaflet')

        :param backend: Widget backend to use: 'bqplot', 'ipyleaflet', 'ipyvolume', 'matplotlib'

        """
        import vaex.jupyter.plot
        backend = vaex.jupyter.plot.create_backend(backend)
        cls = vaex.jupyter.plot.get_type(type)
        x = _ensure_strings_from_expressions(x)
        y = _ensure_strings_from_expressions(y)
        z = _ensure_strings_from_expressions(z)
        for name in 'vx vy vz'.split():
            if name in kwargs:
                kwargs[name] = _ensure_strings_from_expressions(kwargs[name])
        plot2d = cls(backend=backend, dataset=self, x=x, y=y, z=z, grid=grid, shape=shape, limits=limits, what=what,
                     f=f, figure_key=figure_key, fig=fig,
                     selection=selection, grid_before=grid_before,
                     grid_limits=grid_limits, normalize=normalize, colormap=colormap, what_kwargs=what_kwargs, **kwargs)
        if show:
            plot2d.show()
        return plot2d
Viz 1d, 2d or 3d in a Jupyter notebook

        .. note::
            This API is not fully settled and may change in the future

        Example:

        >>> df.plot_widget(df.x, df.y, backend='bqplot')
        >>> df.plot_widget(df.pickup_longitude, df.pickup_latitude, backend='ipyleaflet')

        :param backend: Widget backend to use: 'bqplot', 'ipyleaflet', 'ipyvolume', 'matplotlib'