ScatterWidget¶
-
class
pandas_visual_analysis.widgets.scatter.
ScatterWidget
(data_source, row, index, relative_size, max_height)[source]¶ Bases:
pandas_visual_analysis.widgets.base_widget.BaseWidget
The ScatterWidget displays a scatter plot to highlight the relation between two numerical, time-based or categorical dimensions. In addition to selecting the x- and y-axis, it is also possible show an additional dimension as the size.
- Parameters
data_source (
DataSource
) –pandas_visual_analysis.data_source.DataSource
for the widget.row (
int
) – The row the widget is in.index (
int
) – Index of the row the widget is in.relative_size (
float
) – The space the widget has in a row which is then converted to the width. (e.g. 0.33 => 33%)max_height (
int
) – height in pixels the plot has to have
-
build
()[source]¶ This method returns an IPython Widget root node containing all the children for this widget.
-
observe_brush_indices_change
(sender)[source]¶ This method observes the changes in the brush selection. In order to actually observe changes it has to be registered in
set_observers()
.- Parameters
sender – The instance that sent the signal.
-
on_deselection
(trace, points)[source]¶ This method implements the behaviour of changes in the deselection of this plot. Should reset the brushed selection of
pandas_visual_analysis.data_source.DataSource
in order to propagate the change.- Parameters
trace – The trace object which triggered the deselection.
points – The object containing the points in the ‘point_inds’ field.
-
on_selection
(trace, points, state)[source]¶ This method implements the behaviour of changes in the selection of this plot. Should set the brushed indices property of
pandas_visual_analysis.data_source.DataSource
in order to propagate the change.- Parameters
trace – The trace object which triggered the selection.
points – The object containing the points in the ‘point_inds’ field.
state – State of the input device.