Tabulator makes wrong selection when combined with a filter

[fogo5]

Description of expected behavior and the observed behavior

The tabulator widget makes the wrong selection when combined with a filter.

If the table get filted, the selected row is based on the row number selected and not the actual row selected. See screenshots.

The expected behavior: The filtered table, when selected should provide selection and selected_dataframe based on the shown filtered table.

Complete, minimal, self-contained example code that reproduces the issue

import panel as pn
import pandas as pd
pn.extension('tabulator')


df = pd.DataFrame([['a', 'b', 'c', 'd', 'e'],[1,2,3,5,6]], index = ['name', 'num1']).T
table_widget = pn.widgets.Tabulator(df, disabled = True)
num1_slider = pn.widgets.IntRangeSlider(start=1, end=6, name='num1')
table_widget.add_filter(num1_slider, 'num1')
pn.Row(num1_slider, table_widget)


table_widget.selected_dataframe
table_widget.selection

Screenshots or screencasts of the bug in action

Working example with NO filtering:

After filtering, it no longer works:

Software version info

Mozilla Firefox - 91.0 (64-bit)
Google Chrome - Version 92.0.4515.131 (Official Build) (64-bit)

bokeh 2.3.3 py39h06a4308_0
conda 4.10.3 py39hf3d152e_0 conda-forge
ipykernel 6.1.0 py39hef51801_0 conda-forge
ipython 7.26.0 py39hef51801_0 conda-forge
jupyter_client 6.1.12 pyhd8ed1ab_0 conda-forge
jupyter_core 4.7.1 py39hf3d152e_0 conda-forge
jupyter_server 1.10.2 pyhd8ed1ab_0 conda-forge
jupyterlab 3.1.6 pyhd8ed1ab_0 conda-forge
jupyterlab_server 2.7.0 pyhd8ed1ab_0 conda-forge
numpy 1.20.3 py39hf144106_0
pandas 1.3.1 py39h8c16a72_0
panel 0.12.1 py_0 pyviz
param 1.11.1 py_0 pyviz
python 3.9.1 hdb3f193_2
tornado 6.1 py39h3811e60_1 conda-forge

[Stubatiger]

Seems like that here

  @property
  def selected_dataframe(self):
      """
      Returns a DataFrame of the currently selected rows.
      """

      if not self.selection:
          return self.value
      return self.value.iloc[self.selection]

we select by value and not via the filtered dataframe.
I see several ways to fix that, but not sure what is the best way to go.

We could use the _filter_dataframe function

   self._filter_dataframe(self.value).iloc[self.selection]

but i guess computing that for every access seems too heavy

or we could use the underlying self._processed attribute which seems to hold the filtered dataframe from the self._get_data() function, but not sure if we are allowed to access that.

   self._processed.iloc[self.selection]

[philippjfr]

I think the latter option (i.e. using self._processed) is the right fix.