def histogram(self, x, limits=None, selection=None, selection_interact='default', toolbar=True, shared=False, **kwargs): import vaex.jupyter.model import vaex.jupyter.view if selection is not None: selection = selection.copy() x, = self._axes([x], limits) model = vaex.jupyter.model.Histogram( df=self.df, x=x, selection=selection, selection_interact=selection_interact, **kwargs) if shared: grid = self.grid else: grid = vaex.jupyter.model.GridCalculator(self.df, []) grid.model_add(model) viz = vaex.jupyter.view.Histogram(model=model) if toolbar: viz.toolbar = _add_toolbar(viz) return viz
def data_array(self, axes=[], selection=None, shared=False, display_function=IPython.display.display, **kwargs): '''Create a :func:`vaex.jupyter.model.DataArray` model and :func:`vaex.jupyter.view.DataArray` widget and links them. This is a convenience method to create the model and view, and hook them up. ''' import vaex.jupyter.model import vaex.jupyter.view if selection is not None: selection = selection.copy() model = vaex.jupyter.model.DataArray(df=self.df, axes=axes, selection=selection, **kwargs) if shared: grid = self.grid else: grid = vaex.jupyter.model.GridCalculator(self.df, []) grid.model_add(model) view = vaex.jupyter.view.DataArray(model=model, display_function=display_function) return view
def heatmap(self, x, y, limits=None, selection=None, selection_interact='default', transform='log', toolbar=True, shape=256, shared=False, **kwargs): import vaex.jupyter.model import vaex.jupyter.view x, y = self._axes([x, y], limits) if selection is not None: selection = selection.copy() model = vaex.jupyter.model.Heatmap(df=self.df, x=x, y=y, selection=selection, shape=shape, **kwargs) if shared: grid = self.grid else: grid = vaex.jupyter.model.GridCalculator(self.df, []) self._last_grid = grid grid.model_add(model) viz = vaex.jupyter.view.Heatmap(model=model, transform=transform) if toolbar: viz.toolbar = _add_toolbar(viz) return viz
def pie(self, x, limits=None, shared=False, **kwargs): import vaex.jupyter.model import vaex.jupyter.view x, = self._axes([x], limits) model = vaex.jupyter.model.Histogram(df=self.df, x=x, **kwargs) if shared: grid = self.grid else: grid = vaex.jupyter.model.GridCalculator(self.df, []) grid.model_add(model) viz = vaex.jupyter.view.PieChart(model=model) return viz
def histogram(self, x, limits=None, selections=[None, True], toolbar=True, shared=False, **kwargs): import vaex.jupyter.model import vaex.jupyter.view selections = selections.copy() x, = self._axes([x], limits) model = vaex.jupyter.model.Histogram(df=self.df, x=x, selections=selections, **kwargs) if shared: grid = self.grid else: grid = vaex.jupyter.model.GridCalculator(self.df, []) grid.model_add(model) viz = vaex.jupyter.view.Histogram(model=model) if toolbar: viz.toolbar = _add_toolbar(viz) return viz