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Select column from uploaded csv as a dropdown and plot them

I can see a lot of post with similar or even same problem but I am still unable to solve the issu, sorry for spamming. With plotly-dash I am able to plot a figure by selecting a column of a hard-coded csv. I have tried different examples and now I am also able to print/plot csv from an uploaded file. However, I want to upload a csv and in a dropdown menu, I want to be able to select a column and plot it.

With this I was able to plot line as well as box plot from a hard coded csv by choosing a column from a dropdown menu.

df = pd.read_csv('df_anomaly.csv')


    html.Div([
            html.H3([
                dcc.Dropdown(
                    id = 'Dropdown',
                    options=[{'label': k, 'value': k} for k in list(df.columns.values)[1:]],
                    value='a',
                    placeholder="Name"),
            ]),
            
        ], className = "filter"),
    

    
    html.Div([
         html.Div([
            html.Div([
                dcc.Graph(id='Lineplot'),
            ], style={'width': '75%','display': 'inline-block', 'marginLeft': '15', 'marginTop': '15'}),
            
            html.Div([
                dcc.Graph(id='Boxplot')
            ], style={'width': '23.8%', 'display': 'inline-block', 'marginRight': '15','marginTop': '15','float':'right'})], style={
             'padding': '10px 15px'
         }),
        
    ], style={'padding': '5px 0px','backgroundColor': colors['grey'], 'marginTop': '8', 'marginBottom': '8'})
    
    ])

# Updating Observed Data Plot
@app.callback(
    dash.dependencies.Output('Lineplot', 'figure'),
    [dash.dependencies.Input('Dropdown', 'value')])

def update_graph(selector):
    df_selected = init_calc(selector)
    
    return {
        'data': [go.Scatter(
            y = np.array(df_selected['selected']),
            mode = 'lines',
            line = dict(
                color = colors['red']
            )
        )],
        'layout': go.Layout(
            height=400,
            title=go.layout.Title(
                text='Line Plot',
                font=dict(
                    color = colors['black'],
                )
            ),
            xaxis=dict(
                title='x',
                linecolor = colors['black'],
                color = colors['black'],
                ticks='inside',
                zeroline = False,
            ),
            yaxis=dict(
                title='y',
                linecolor = colors['black'],
                color = colors['black'],
                ticks='inside',
                zeroline = False,
            ),
            hovermode='closest',
        )
    }

# Updating Boxplot
@app.callback(
    dash.dependencies.Output('Boxplot', 'figure'),
    [dash.dependencies.Input('Dropdown', 'value')])

def update_boxplot(selector):
    
    df_selected = init_calc(selector)
    
    return {
        'data': [go.Box(
            name='',
            y=df_selected['selected'],
            marker = dict(
                color = colors['orange']
            )
        )],
        'layout': go.Layout(
            height=400,
            title=go.layout.Title(
                text='Boxplot', 
                font=dict(
                    color = colors['black'],
                )
            ),
            xaxis=dict(
                linecolor = colors['black'],
                color = colors['black'],
                zeroline = False,
            ),
            yaxis=dict(
                title='Traffic',
                linecolor = colors['black'],
                color = colors['black'],
                zeroline = False,
                ticks='inside',
            ),
        ),
    }

def init_calc(selector):
    df_selected = pd.DataFrame(columns=['selected'])
    df_selected['selected'] = df[str(selector)]
    return df_selected

#------------------------------------------------------------------------------------
# Running the App
if __name__ == '__main__':
    app.run_server(debug=False)

Also, If I add this bit of code I can print the uploaded csv:

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': '2px'
        },
        # 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.fromtimestamp(date)),

        dash_table.DataTable(
            data=df[:5].to_dict('records'),
            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

with the little tweak I can also manually choose the column and plot the column of the uploaded csv but I want to be able to select a column of uploaded csv as I did with the hardcoded one. How can I do that?

Thanks in advance