I am developing a dashboard in Dash with Python and in one of the core components I am trying to upload a csv file and display it in a datatable format (see below). That works well (see picture), I followed this example: dcc.Upload | Dash for Python Documentation | Plotly
However, I would also like to use the table as a pandas DataFrame later in the code. Since I upload the csv file after I’ve run the code for the dashboard (deployed on the development server), I could not find a way to return the csv contents as a DataFrame. Any way in which this can be done? My code is below.
NB! I checked the forum for topics similar to this, but I could not find a clear solution.
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.' ]) trade_upload = pd.DataFrame(df) return dbc.Table.from_dataframe(trade_upload) @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(port=8051, debug=False)