Plotly-Dash：为每个选定的 df 列添加新的 yaxis

Question

I have a basic dash app that graphs some data from a dictionary of dataframes. The first dropdown selects the df, while the second selects the columns of the df to be plotted.

This works well, but I can't seem to add a new yaxis for each of the plotted columns. I have a large number of columns in each df and they change depending on the df that is selected.

First, I tried to change the updateGraph callback to include yaxis=i after defining x, y & name. Looking at the documentation, it seems that I can define the yaxis in go.Scatter but that I would need to set them as 'y2', 'y3, 'y4' etc. I've also tried to update the layout via go.Figure.add_trace in this way but neither has worked. The code is below, where dict_main is a dictionary of dataframes of various sizes.

All help is appreciated!

data = list(dict_main.keys())
channels = dict_main[data[0]]

app.layout = html.Div(
    [
        html.Div([
            dcc.Dropdown(
                id='data-dropdown',
                options=[{'label': speed, 'value': speed} for speed in data],
                value=list(dict_main.keys())[0],
                searchable=False
            ),
        ], style={'width': '49%', 'display': 'inline-block'}),
        html.Div([
            dcc.Dropdown(
                id='channel-dropdown',
                multi=True
            ),
        ], style={'width': '49%', 'display': 'inline-block'}
        ),
        html.Div([
            dcc.Graph(
                id='Main-Graph',
            ),
        ], style={'width': '98%', 'display': 'inline-block'}
        )
    ]
)

@app.callback(
    Output('channel-dropdown', 'options'),
    [Input('data-dropdown', 'value')])
def update_date_dropdown(speed):
    return [{'label': i, 'value': i} for i in dict_main[speed]]

@app.callback(
    Output('Main-Graph', 'figure'),
    [Input('channel-dropdown', 'value')],
    [State('data-dropdown', 'value')])
def updateGraph(channels, speed):
    if channels:

        return go.Figure(data=[go.Scatter(x=dict_main[speed].index, y=dict_main[speed][i], name=i, yaxis='y2') for i in channels])
    else:
        return go.Figure(data=[])

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

UPDATE, This works; although some small changes to color and position are still needed - Thanks to @Philipp for all the help;

@app.callback(
    Output('Main-Graph', 'figure'),
    [Input('channel-dropdown', 'value')],
    [State('rpm-dropdown', 'value')])
def updateGraph(channels, test):
    if channels:
        j=1
        my_layout = {}
        my_axis = list("")
        for index, column in enumerate(list(channels)):
            my_layout['yaxis' + str(j) if j > 1 else 'yaxis'] = {}
            my_layout['yaxis' + str(j) if j > 1 else 'yaxis']['title'] = column
            my_layout['yaxis' + str(j) if j > 1 else 'yaxis']['overlaying'] = 'y' if j > 1 else 'free'
            my_layout['yaxis' + str(j) if j > 1 else 'yaxis']['anchor'] = 'free'
            my_layout['yaxis' + str(j) if j > 1 else 'yaxis']['side'] = 'left'
            my_axis.append('y' + str(j) if j > 1 else 'y')
            j+=1
        return go.Figure(data=[go.Scatter(x=dict_main[test].index, y=dict_main[test][column], name=column, yaxis=my_axis[index]) for index, column in enumerate(channels)],layout=my_layout)

    else:
        return go.Figure(data=[])

Answer 1

You have to define every y-axis in the layout property of your graph (right now you're only setting the data property). See this example .

If you don't want to draw all y-axes (if your df has many columns) you have to set some of them invisible via setting variables like [overlaying, ticks, showticklabels, showgrid, zeroline] (you can find info about them here ) but they still have to be defined accordingly in the layout so you can refer to them in the scatter function.