bokeh.core.properties.field

Here are the examples of the python api bokeh.core.properties.field taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

3 Examples 7

3 Source : test_annotations.py
with MIT License
from rthorst

def test_legend_item_with_field_label_and_different_data_sources_raises_a_validation_error():
    legend_item = LegendItem()
    gr_1 = GlyphRenderer(data_source=ColumnDataSource(data={'label': [1]}))
    gr_2 = GlyphRenderer(data_source=ColumnDataSource(data={'label': [1]}))
    legend_item.label = field('label')
    legend_item.renderers = [gr_1, gr_2]
    with mock.patch('bokeh.core.validation.check.log') as mock_logger:
        check_integrity([legend_item])
        assert mock_logger.error.call_count == 1


def test_legend_item_with_value_label_and_different_data_sources_does_not_raise_a_validation_error():

0 Source : test_annotations.py
with MIT License
from rthorst

def test_legend_item_with_field_label_raises_error_if_field_not_in_cds():
    legend_item = LegendItem()
    gr_1 = GlyphRenderer(data_source=ColumnDataSource())
    legend_item.label = field('label')
    legend_item.renderers = [gr_1]
    with mock.patch('bokeh.core.validation.check.log') as mock_logger:
        check_integrity([legend_item])
        assert mock_logger.error.call_count == 1

#-----------------------------------------------------------------------------
# Dev API
#-----------------------------------------------------------------------------

#-----------------------------------------------------------------------------
# Private API
#-----------------------------------------------------------------------------

#-----------------------------------------------------------------------------
# Code
#-----------------------------------------------------------------------------

0 Source : plot.py
with Apache License 2.0
from spotify

    def bar(self,
            data_frame,
            categorical_columns,
            numeric_column,
            color_column=None,
            color_order=None,
            categorical_order_by='values',
            categorical_order_ascending=False):
        """Bar chart.

        Note:
            To change the orientation set x_axis_type or y_axis_type
            argument of the Chart object.

        Args:
            data_frame (pandas.DataFrame): Data source for the plot.
            categorical_columns (str or list): Column name to plot on
                the categorical axis.
            numeric_column (str): Column name to plot on the numerical axis.
            color_column (str, optional): Column name to group by on
                the color dimension.
            color_order (list, optional): List of values within the
                'color_column' for specific color sort.
            categorical_order_by (str or array-like, optional):
                Dimension for ordering the categorical axis. Default 'values'.
                - 'values': Order categorical axis by the numerical
                    axis values. Default.
                - 'labels': Order categorical axis by the categorical labels.
                - array-like object (list, tuple, np.array): New labels
                    to conform the categorical axis to.
            categorical_order_ascending (bool, optional): Sort order of the
                categorical axis. Default False.
        """
        vertical = self._chart.axes._vertical

        source, factors, _ = self._construct_source(
            data_frame,
            categorical_columns,
            numeric_column,
            categorical_order_by=categorical_order_by,
            categorical_order_ascending=categorical_order_ascending,
            color_column=color_column)

        colors, color_values = self._get_color_and_order(
            data_frame, color_column, color_order, categorical_columns)

        if color_column is None:
            colors = colors[0]

        self._set_categorical_axis_default_factors(vertical, factors)
        self._set_categorical_axis_default_range(vertical, data_frame,
                                                 numeric_column)
        bar_width = self._get_bar_width(factors)

        if color_column:
            legend = bokeh.core.properties.field('color_column')
            legend = 'color_column'
        else:
            legend = None

        if vertical:
            self._plot_with_legend(
                self._chart.figure.vbar,
                legend_group=legend,
                x='factors',
                width=bar_width,
                top=numeric_column,
                bottom=0,
                line_color='white',
                source=source,
                fill_color=colors,
                )

        else:

            self._plot_with_legend(
                self._chart.figure.hbar,
                legend_group=legend,
                y='factors',
                height=bar_width,
                right=numeric_column,
                left=0,
                line_color='white',
                source=source,
                fill_color=colors,
                )

        # Set legend defaults if there are multiple series.
        if color_column is not None:
            self._chart.style._apply_settings('legend')
        return self._chart

    def interval(self,