向Plotly添加辅助轴

Question

我比较两个不同的数据集，我需要添加一个次要的y轴来查看第二个数据集。FX2（第一组）的Y值指数大于BLX1（第二组）。两个集合都包含一个“G”列的相同值，小部件应该能够根据“G”列对这两个集合进行图形化（请检查这一点）

这是我的密码：

        month = widgets.IntSlider(
            value=1.0,
            min=1.0,
            max=12.0,
            step=1.0,
            description='Month:',
            continuous_update=False
        )

        use_date = widgets.Checkbox(
            description='Date: ',
            value=True,
        )

        container = widgets.HBox(children=[use_date, month])

        textbox = widgets.Dropdown(
            description='Client FX:   ',
            value= "123456 " ,
            options=fx2['G'].unique().tolist(),
        )

        origin = widgets.Dropdown(
            options=list(blx1['G'].unique()),
            value="123456 " ,
            description='ClientBalance:',
        )


        # Assign an empty figure widget with two traces
        trace1 = go.Scattergl(x=fx2.index, y=fx2['buy_flow'], opacity=0.75, name='FX', mode= 'markers', secondary_y=True)
        trace2 = go.Histogram(x=blx1.index, y=blx1['bal'], opacity=0.75, name='Balance')
        g = go.FigureWidget(data=[trace1, trace2],
                            layout=go.Layout(
                                title=dict(
                                    text='Client Analysis'
                                ),
                                barmode='overlay'
                            ))
    def validate():
        if origin.value in blx1['G'].unique() and textbox.value in fx2['G'].unique():
            return True
        else:
            return False


    def response(change):
        if validate():
            if use_date.value:
                filter_list = [i and j and k for i, j, k in
                               zip(fx2.index == month.value, fx2.index == textbox.value,
                                   blx1.index == origin.value)]
                temp_df = df[filter_list]

            else:
                filter_list = [i and j for i, j in
                               zip( fx2['G'] == "123456" , blx1['G'] == "123456")]
                temp_df = df[filter_list]
            x1 = temp_df['arr_delay']
            x2 = temp_df['dep_delay']
            with g.batch_update():
                g.data[0].x = x1
                g.data[1].x = x2
                g.layout.barmode = 'overlay'
                g.layout.xaxis.title = 'Date'
                g.layout.yaxis.title = 'Value'


    origin.observe(response, names="value")
    textbox.observe(response, names="value")
    month.observe(response, names="value")
    use_date.observe(response, names="value")
def validate():
    if origin.value in blx1['G'].unique() and textbox.value in fx2['G'].unique():
        return True
    else:
        return False


def response(change):
    if validate():
        if use_date.value:
            filter_list = [i and j and k for i, j, k in
                           zip(fx2.index == month.value, fx2.index == textbox.value,
                               blx1.index == origin.value)]
            temp_df = df[filter_list]

        else:
            filter_list = [i and j for i, j in
                           zip( fx2['G'] == 123456 , blx1['G'] == 123456)]
            temp_df = df[filter_list]
        x1 = temp_df['arr_delay']
        x2 = temp_df['dep_delay']
        with g.batch_update():
            g.data[0].x = x1
            g.data[1].x = x2
            g.layout.barmode = 'overlay'
            g.layout.xaxis.title = 'Date'
            g.layout.yaxis.title = 'Values'


origin.observe(response, names="value")
textbox.observe(response, names="value")
month.observe(response, names="value")
use_date.observe(response, names="value")

container2 = widgets.HBox([origin, textbox])
widgets.VBox([container,
              container2,
              g])