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python - Bokeh DataTable - Return row and column on selection callback

Using an on_change callback, I can get the numerical row index of a selection within a DataTable, in Bokeh. Is it possible to: a) Get the column index b) Get the values of the indexes (column and row headers)

Example code:

from bokeh.io import curdoc
from bokeh.layouts import row, column
import pandas as pd
from bokeh.models import ColumnDataSource, ColorBar, DataTable, DateFormatter, TableColumn, HoverTool, Spacer, DatetimeTickFormatter

'''
Pandas
'''

df = pd.DataFrame(data = {'Apples': [5,10], 'Bananas': [16,15], 'Oranges': [6,4]})
df.rename(index={0:'A',1:'B'}, inplace=True)

'''
BOKEH
'''

sourceTableSummary = ColumnDataSource(df)
Columns = [TableColumn(field=colIndex, title=colIndex) for colIndex in df.columns] 
data_table = DataTable(columns=Columns, source=sourceTableSummary, index_position = 0, width = 1900, height = 200, fit_columns=False) 

'''
Funcs
'''

def return_value(attr, old, new):
    selectionRowIndex=sourceTableSummary.selected.indices[0]
    print("Selected Row Index ", str(selectionRowIndex))
    selectionValue=sourceTableSummary.data['Apples'][selectionRowIndex]
    print("Selected value for Apples ", str(selectionValue))
    # selectionColumnIndex?
    # selectionRowHeader?
    # selectionColumnHeader?


sourceTableSummary.on_change('selected', return_value)

curdoc().add_root(column(children=[data_table]))

This gives the following which can returns rows, and the values within the selection. This is ideal if I always want a single column returned. However the selection UI (dotted line) seems to suggest that the specific column is known, not just the row. If there's no way of attaining the selected column, can I look it up using both the Row Index and the Cell Value?

Local Server Output & Table

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by (71.8m points)

The following code uses JS callback to show the row and column index as well as the cell contents. The second Python callback is a trick to reset the indices so that a click on the same row can be detected (tested with Bokeh v1.0.4). Run with bokeh serve --show app.py

from random import randint
from datetime import date
from bokeh.models import ColumnDataSource, TableColumn, DateFormatter, DataTable, CustomJS
from bokeh.layouts import column
from bokeh.models.widgets import TextInput
from bokeh.plotting import curdoc

source = ColumnDataSource(dict(dates = [date(2014, 3, i + 1) for i in range(10)], downloads = [randint(0, 100) for i in range(10)]))
columns = [TableColumn(field = "dates", title = "Date", formatter = DateFormatter()), TableColumn(field = "downloads", title = "Downloads")]
data_table = DataTable(source = source, columns = columns, width = 400, height = 280, editable = True, reorderable = False)

text_row = TextInput(value = None, title = "Row index:", width = 420)
text_column = TextInput(value = None, title = "Column Index:", width = 420)
text_date = TextInput(value = None, title = "Date:", width = 420)
text_downloads = TextInput(value = None, title = "Downloads:", width = 420)
test_cell = TextInput(value = None, title = "Cell Contents:", width = 420)

source_code = """
var grid = document.getElementsByClassName('grid-canvas')[0].children;
var row, column = '';

for (var i = 0,max = grid.length; i < max; i++){
    if (grid[i].outerHTML.includes('active')){
        row = i;
        for (var j = 0, jmax = grid[i].children.length; j < jmax; j++)
            if(grid[i].children[j].outerHTML.includes('active')) 
                { column = j }
    }
}
text_row.value = String(row);
text_column.value = String(column);
text_date.value = String(new Date(source.data['dates'][row]));
text_downloads.value = String(source.data['downloads'][row]); 
test_cell.value = column == 1 ? text_date.value : text_downloads.value; """

def py_callback(attr, old, new):
    source.selected.update(indices = [])

source.selected.on_change('indices', py_callback)
callback = CustomJS(args = dict(source = source, text_row = text_row, text_column = text_column, text_date = text_date, text_downloads = text_downloads, test_cell = test_cell), code = source_code)
source.selected.js_on_change('indices', callback)
curdoc().add_root(column(data_table, text_row, text_column, text_date, text_downloads, test_cell))

Result:

enter image description here


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