import datetime as dt
import pandas as pd
import panel as pn

pn.extension()

df = pd.DataFrame({
    'int': [1, 2, 3],
    'float': [3.14, 6.28, 9.42],
    'str': ['A', 'B', 'C'],
    'bool': [True, False, True],
    'date': [dt.date(2019, 1, 1), dt.date(2020, 1, 1), dt.date(2020, 1, 10)],
    'datetime': [dt.datetime(2019, 1, 1, 10), dt.datetime(2020, 1, 1, 12), dt.datetime(2020, 1, 10, 13)]
}, index=[1, 2, 3])

df_widget = pn.widgets.DataFrame(df, name='DataFrame')

df_widget

from bokeh.models.widgets.tables import SelectEditor, NumberFormatter

editor = SelectEditor(options=['A', 'B', 'C', 'D'])
formatter = NumberFormatter(format='0.00000') 

table = pn.widgets.DataFrame(df, editors={'str': editor}, formatters={'float': formatter})
table

table.selection = [0, 2]

table.selected_dataframe

pn.widgets.DataFrame(df, autosize_mode='none', widths={'index': 50, 'int': 50, 'float': 50, 'str': 70, 'bool': 130}, width=350)

pn.widgets.DataFrame(df, autosize_mode='fit_columns', width=300)

pn.widgets.DataFrame(df, autosize_mode='fit_viewport')

date_df = df.set_index('datetime').iloc[:5, :2]

pn.widgets.DataFrame(date_df, height=400, widths=150, frozen_columns=1, autosize_mode='none')

agg_df = pd.concat([date_df, date_df.median().to_frame('Median').T, date_df.mean().to_frame('Mean').T])
agg_df.index= agg_df.index.map(str)

pn.widgets.DataFrame(agg_df, frozen_rows=-2, height=400)

from bokeh.sampledata.population import data as population_data 

pop_df = population_data[population_data.Year == 2020].set_index(['Location', 'AgeGrp', 'Sex'])[['Value']]

pn.widgets.DataFrame(value=pop_df, hierarchical=True, aggregators={'Sex': 'sum', 'AgeGrp': 'sum'}, height=400)

import numpy as np

stream_df = pd.DataFrame(np.random.randn(10, 5), columns=list('ABCDE'))

stream_table = pn.widgets.DataFrame(stream_df, autosize_mode='fit_columns', width=450)
stream_table

def stream_data():
    stream_df = pd.DataFrame(np.random.randn(10, 5), columns=list('ABCDE'))
    stream_table.stream(stream_df)

pn.state.add_periodic_callback(stream_data, period=1000, count=5)

patch_table = pn.widgets.DataFrame(df[['int', 'float', 'str', 'bool']])
patch_table

patch_table.patch({
    'bool': [
        (0, False),
        (2, False)
    ],
    'int': [
        (slice(0, 2), [3, 2])
    ]
}, as_index=False)

pn.Row(df_widget.controls(jslink=True), df_widget)