Populate DataTable from styled Pandas DataFrame

[davetapley]

Pandas has nice Table Visualization features, which come with built in formatting functionality.

Currently it can write to HTML, LaTeX, etc. (which it does via jinja templates),
but it would be cool if it could also populate a DataTable.

---

Here's my hack solution for now, if there's more interest perhaps we can come up with something more robust?

from pandas.io.formats.style_render import StylerRenderer

from textual.widgets import DataTable
from textual.widgets.data_table import RowKey


def df_to_dt(s: StylerRenderer, dt: DataTable) -> list[RowKey]:
    d = s._render(True, True)  # type: ignore
    head = d['head'][0]
    body = d['body']
    cols = [c['display_value'] for c in head if c['is_visible']]
    rows = [[c['display_value'] for c in r if c['is_visible']] for r in body]

    dt.add_columns(*cols)
    return dt.add_rows(rows

import unittest
from unittest.mock import Mock

from pandas import DataFrame, to_datetime

from gui.lib import df_to_dt


class TestLib(unittest.TestCase):
    def test_df_to_dt(self):
        # https://stackoverflow.com/a/60273382/21115
        df = DataFrame({'DOB': {0: '2023-01-02', 1: '2023-01-03'}})
        df['DOB'] = to_datetime(df.DOB)

        s = df.style.hide(axis="index").format(
            {"DOB": lambda t: t.strftime("%m-%d-%Y")})  # type: ignore

        dt = Mock()

        df_to_dt(s, dt)

        dt.add_columns.assert_called_once_with('DOB')
        dt.add_rows.assert_called_once_with([['01-02-2023'], ['01-03-2023']])