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Updated documentation on using `dcc.Upload` with `dash_table.DataTable`?

The upload component documentation has an example with the old datatable experiment and not the new datatable. The example in the new datatable documentation doesnt end up showing an actual table, only a graph. Is there a working example with these 2 components somewhere else?

Any there any plans to update the documentation to reflect the new components, replacing the old table experiment and hidden divs?

Thanks for reporting! I translated those examples from the old datatable to the new datatable this weekend (https://github.com/plotly/dash-docs/pull/305) but forgot to add the “columns” prop. Here’s a new PR with the fix: https://github.com/plotly/dash-docs/pull/310, it should get in tonite or tomorrow. In the meantime, here’s the corrected example for you:

import base64
import datetime
import io

import dash
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_html_components as html
import dash_table

import pandas as pd


external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div([
    dcc.Upload(
        id='upload-data',
        children=html.Div([
            'Drag and Drop or ',
            html.A('Select Files')
        ]),
        style={
            'width': '100%',
            'height': '60px',
            'lineHeight': '60px',
            'borderWidth': '1px',
            'borderStyle': 'dashed',
            'borderRadius': '5px',
            'textAlign': 'center',
            'margin': '10px'
        },
        # Allow multiple files to be uploaded
        multiple=True
    ),
    html.Div(id='output-data-upload'),
])


def parse_contents(contents, filename, date):
    content_type, content_string = contents.split(',')

    decoded = base64.b64decode(content_string)
    try:
        if 'csv' in filename:
            # Assume that the user uploaded a CSV file
            df = pd.read_csv(
                io.StringIO(decoded.decode('utf-8')))
        elif 'xls' in filename:
            # Assume that the user uploaded an excel file
            df = pd.read_excel(io.BytesIO(decoded))
    except Exception as e:
        print(e)
        return html.Div([
            'There was an error processing this file.'
        ])

    return html.Div([
        html.H5(filename),
        html.H6(datetime.datetime.fromtimestamp(date)),

        dash_table.DataTable(
            data=df.to_dict('rows'),
            columns=[{'name': i, 'id': i} for i in df.columns]
        ),

        html.Hr(),  # horizontal line

        # For debugging, display the raw contents provided by the web browser
        html.Div('Raw Content'),
        html.Pre(contents[0:200] + '...', style={
            'whiteSpace': 'pre-wrap',
            'wordBreak': 'break-all'
        })
    ])


@app.callback(Output('output-data-upload', 'children'),
              [Input('upload-data', 'contents')],
              [State('upload-data', 'filename'),
               State('upload-data', 'last_modified')])
def update_output(list_of_contents, list_of_names, list_of_dates):
    if list_of_contents is not None:
        children = [
            parse_contents(c, n, d) for c, n, d in
            zip(list_of_contents, list_of_names, list_of_dates)]
        return children



if __name__ == '__main__':
    app.run_server(debug=True)