Plotly 图形具有相同的 X 轴和多个 Y 轴，数据数量未定义

Question

I've developed a software that reads data from csv file and show data in a chart with multiple Y axes. For each signal in my csv file I have a line in the chart and for each line in the chart there is an axes.

If the number of signals contained in csv file is unknown, so there are more than six for example (S1...S7,S8,S9,etc....), how can I auto generate Y axis for each signal??

Now my program is build like I know the number of signals in the csv file. I've already tried to create a for that modify the keyword yaxis but is not possible.

My csv file:

DateTime;S1;S2;S3;S4;S5;S6
2020-07-17 09:57:27.119916;725.9926027110598;730.5730869210306;946.2937510737263;542.341137182406;758.5531610786929;512.2027881299339
2020-07-17 09:57:28.119916;761.1846087077208;984.1009029835216;974.8724733720549;576.8019892357476;751.6553704523698;855.5439493088621
2020-07-17 09:57:29.119916;618.7837289058051;823.9970681226491;594.2841714340789;873.3093170922189;770.0875733375253;681.1715820388949
2020-07-17 09:57:30.119916;515.9456035777555;533.017970929369;639.3409213385498;542.4405737836958;514.4985515824058;650.5229638670448
2020-07-17 09:57:31.119916;589.1350057317254;605.703259361724;602.3181712775759;860.9749699475683;801.7960812507487;562.400896160191
2020-07-17 09:57:32.119916;626.2528314431347;615.7078057434281;643.2023497200336;709.6997180536518;741.365852401098;712.4384053449293
2020-07-17 09:57:33.119916;553.9768845577024;961.7714859567449;519.8207498752649;551.8006708566627;511.7426656331682;849.3428394570542
2020-07-17 09:57:34.119916;994.8208541190293;700.59423301376;569.1853469890981;997.5842090634065;621.2070112896865;848.5079857917269
2020-07-17 09:57:35.119916;502.2301607876932;760.8787524302393;671.2907579865052;669.0718770518221;901.3788876259023;926.077760311429
2020-07-17 09:57:36.119916;578.3978109170034;811.407262562966;822.6244615030105;570.0016494663124;935.0853062150045;689.8800124555897

My code:

df = pd.read_csv(file_name, delimiter = ';')
        
        fig = go.Figure()

        for i in range(1, len(df.columns)):
            fig.add_trace(go.Scatter(x=df.iloc[:,0], y=df.iloc[:,i], name=df.columns[i], yaxis='y'+str(i)))
        
        fig.update_layout(
            xaxis=dict(
                domain=[0.3, 0.7]
            ),
            yaxis=dict(
                title="S1",
                titlefont=dict(
                    color="#1f77b4"
                ),
                tickfont=dict(
                    color="#1f77b4"
                ),
                side="left",
                position=0.10        
            ),
            yaxis2=dict(
                title="S2",
                titlefont=dict(
                    color="#ff7f0e"
                ),
                tickfont=dict(
                    color="#ff7f0e"
                ),
                anchor="free",
                overlaying="y",
                side="left",
                position=0.20
            ),
            yaxis3=dict(
                title="S3",
                titlefont=dict(
                    color="#d62728"
                ),
                tickfont=dict(
                    color="#d62728"
                ),
                anchor="x",
                overlaying="y",
                side="left",
                position=0.30
            ),
            yaxis4=dict(
                title="S4",
                titlefont=dict(
                    color="#6427bd"
                ),
                tickfont=dict(
                    color="#6427bd"
                ),
                anchor="free",
                overlaying="y",
                side="right",
                position=0.70
            ),
            yaxis5=dict(
                title="S5",
                titlefont=dict(
                    color="#3758bd"
                ),
                tickfont=dict(
                    color="#3758bd"
                ),
                anchor="free",
                overlaying="y",
                side="right",
                position=0.80
            ),
            yaxis6=dict(
                title="S6",
                titlefont=dict(
                    color="#2690bd"
                ),
                tickfont=dict(
                    color="#2690bd"
                ),
                anchor="free",
                overlaying="y",
                side="right",
                position=0.90
            )
        )
        
        fig.update_layout(
            title_text="Stacked y-axes",
            yaxis={'title':'Values [unit]'}, 
            xaxis={'title':'DateTime'},
            height=600, 
            width=1000
        )
        
        plot(fig)

This is my result now: https://drive.google.com/file/d/1QPLG0gT2SvWd4_0-piGQsdRy_eTACFn1/view?usp=sharing

Answer 1

You can build all the yaxis* arguments inside your for loop. In the example below, I create a dict named axes , add each yaxis* subdict and later I call fig.update_layouts(**axes) .

df = pd.read_csv('filename.csv', delimiter = ';')
        
fig = go.Figure()

colors=["#1f77b4","#ff7f0e","#d62728","#6427bd","#3758bd","#2690bd"]

axes = {
    'xaxis': dict(domain=[0.3, 0.7])
}

for i in range(1, len(df.columns)):
    fig.add_trace(go.Scatter(x=df.iloc[:,0], y=df.iloc[:,i], name=df.columns[i], yaxis='y'+str(i)))
    s = 'yaxis'
    if i > 1:
        s = s + str(i)
    axes[s] = dict(
        title=f"S{i}",
        titlefont=dict(color=colors[i-1]),
        tickfont=dict(color=colors[i-1])
    )
    if i > 1:
        axes[s]['anchor'] = 'free'
        axes[s]['overlaying'] = 'y'
    if i > len(df.columns) / 2:
        axes[s]['side'] = 'right'
        axes[s]['position'] = 0.3 + 0.1*i
    else:
        axes[s]['side'] = 'left'
        axes[s]['position'] = 0.1*i

fig.update_layout(**axes)
fig.update_layout(
    title_text="Stacked y-axes",
    yaxis={'title':'Values [unit]'}, 
    xaxis={'title':'DateTime'},
    height=600, 
    width=1000
)