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