Python Dash: loading pandas dataframes into data table

After someone also replied to me on the plotly forums (thankfully), it seems the final answer is to pre-set one's Data Table with the columns of the pandas dataframe that is going to go into it at some point, like this,

dash_table.DataTable(
    id='table',
    columns=[
    {'name': 'Column 1', 'id': 'column1'},
    {'name': 'Column 2', 'id': 'column2'},
    {'name': 'Column 3', 'id': 'column3'},
    {'name': 'Column 4', 'id': 'column4'},
    {'name': 'Column 5', 'id': 'column5'}]
)

, and then send in a dict of your pandas dataframe.

Assuming your tweets function returns a dataframe, adding table columns as a second output to your callback should work.

@app.callback(
    [Output(component_id='tweet_table', component_property='data'),
     Output(component_id='tweet_table', component_property='columns')
    [Input(component_id='screenNames_submit_button', component_property='n_clicks_timestamp')],
    [State(component_id='ScreenName_Input', component_property='value')]
)
def display_tweets(submit_button, screen_names):
    tweets = old_tweets(screen_names)
    columns = [{'name': col, 'id': col} for col in tweets.columns]
    data = tweets.to_dict(orient='records')
    return data, columns