Filter a Bokeh DataTable using multiple filter widgets. Runs in a Jupyter notebook.

bokeh_datatable_filtered.py

import bokeh.embed
import bokeh.io
import bokeh.models
import bokeh.models.widgets
import bokeh.plotting
import pandas as pd
from pandas_datareader import wb

bokeh.plotting.output_notebook()

df = wb.download(indicator='NY.GDP.PCAP.KD', country=['US', 'CA', 'MX'], start=2005, end=2008)
df = df.reset_index()

source = bokeh.models.ColumnDataSource(df)
original_source = bokeh.models.ColumnDataSource(df)
columns = [
    bokeh.models.widgets.TableColumn(field="country", title="Country"),
    bokeh.models.widgets.TableColumn(field="year", title="Year"),
    bokeh.models.widgets.TableColumn(field="NY.GDP.PCAP.KD", title="NY.GDP.PCAP.KD"),
]
data_table = bokeh.models.widgets.DataTable(source=source, columns=columns)

# callback code to be used by all the filter widgets
# requires (source, original_source, country_select_obj, year_select_obj, target_object)
combined_callback_code = """
var data = source.get('data');
var original_data = original_source.get('data');
var country = country_select_obj.get('value');
console.log("country: " + country);
var year = year_select_obj.get('value');
console.log("year: " + year);

for (var key in original_data) {
    data[key] = [];
    for (var i = 0; i < original_data['country'].length; ++i) {
        if ((country === "ALL" || original_data['country'][i] === country) &&
            (year === "ALL" || original_data['year'][i] === year)) {
            data[key].push(original_data[key][i]);
        }
    }
}
target_obj.trigger('change');
source.trigger('change');
"""

# define the filter widgets, without callbacks for now
country_list = ['ALL'] + df['country'].unique().tolist()
country_select = bokeh.models.widgets.Select(title="Country:", value=country_list[0], options=country_list)
year_list = ['ALL'] + df['year'].unique().tolist()
year_select = bokeh.models.widgets.Select(title="Year:", value=year_list[0], options=year_list)

# now define the callback objects now that the filter widgets exist
generic_callback = bokeh.models.CustomJS(
    args=dict(source=source, 
              original_source=original_source, 
              country_select_obj=country_select, 
              year_select_obj=year_select, 
              target_obj=data_table),
    code=combined_callback_code
)

# finally, connect the callbacks to the filter widgets
country_select.callback = generic_callback
year_select.callback = generic_callback

p = bokeh.io.vplot(country_select, year_select, data_table)
bokeh.plotting.show(p)

I have the same problem as @LEEVE, it produces an html but the filtering does not work

JS callbacks in above code snippets are not working as expected. Some necessary changes have been made. It should work under bokeh 1.0.1 env.

from bokeh.layouts import column
from bokeh.models import ColumnDataSource, CustomJS
from bokeh.models.widgets import DataTable, TableColumn, Select
from bokeh.plotting import save, output_file
from pandas_datareader import wb

df = wb.download(indicator='NY.GDP.PCAP.KD', country=['US', 'CA', 'MX'], start=2005, end=2008)
df = df.reset_index()

source = ColumnDataSource(df)
original_source = ColumnDataSource(df)
columns = [
   TableColumn(field="country", title="Country"),
   TableColumn(field="year", title="Year"),
   TableColumn(field="NY.GDP.PCAP.KD", title="NY.GDP.PCAP.KD"),
]
data_table = DataTable(source=source, columns=columns)

# callback code to be used by all the filter widgets
# requires (source, original_source, country_select_obj, year_select_obj, target_object)
combined_callback_code = """
var data = source.data;
var original_data = original_source.data;
var country = country_select_obj.value;
console.log("country: " + country);
var year = year_select_obj.value;
console.log("year: " + year);
for (var key in original_data) {
    data[key] = [];
    for (var i = 0; i < original_data['country'].length; ++i) {
        if ((country === "ALL" || original_data['country'][i] === country) &&
            (year === "ALL" || original_data['year'][i] === year)) {
            data[key].push(original_data[key][i]);
        }
    }
}

source.change.emit();
target_obj.change.emit();
"""

# define the filter widgets, without callbacks for now
country_list = ['ALL'] + df['country'].unique().tolist()
country_select = Select(title="Country:", value=country_list[0], options=country_list)
year_list = ['ALL'] + df['year'].unique().tolist()
year_select = Select(title="Year:", value=year_list[0], options=year_list)

# now define the callback objects now that the filter widgets exist
generic_callback = CustomJS(
    args=dict(source=source, 
              original_source=original_source, 
              country_select_obj=country_select, 
              year_select_obj=year_select, 
              target_obj=data_table),
    code=combined_callback_code
)

# finally, connect the callbacks to the filter widgets
country_select.js_on_change('value', generic_callback)
year_select.js_on_change('value', generic_callback)

p = column(country_select,year_select,data_table)
output_file('datatable_filter.html')
save(p)