Plotly: How to add multiple y-axes?

Here is an example of how multi-level y-axes can be created.

Essentially, the keys to this are:

• Create a key in the layout dict, for each axis, then assign a trace to the that axis.
• Set the xaxis domain to be narrower than [0, 1] (for example [0.2, 1]), thus pushing the left edge of the graph to the right, making room for the multi-level y-axis.

A link to the official Plotly docs on the subject.

To make reading the data easier for this demonstration, I have taken the liberty of storing your dataset as a CSV file, rather than Excel - then used the pandas.read_csv() function to load the dataset into a pandas.DataFrame, which is then passed into the plotting functions as data columns.

Example:

Read the dataset:

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

Sample plotting code:

layout = {'title': '8th Oct BESS'}
traces = []

traces.append({'y': df['storage'], 'name': 'Storage'})
traces.append({'y': df['actual_gen'], 'name': 'Actual Gen'})
traces.append({'y': df['solar_gen'], 'name': 'Solar Gen'})
traces.append({'y': df['total_gen'], 'name': 'Total Gen', 'yaxis': 'y2'})
traces.append({'y': df['frequency'], 'name': 'Frequency', 'yaxis': 'y3'})

layout['xaxis'] = {'domain': [0.12, 0.95]}
layout['yaxis1'] = {'title': 'Actual Gen, Storage, Solar Gen', 'titlefont': {'color': 'orange'}, 'tickfont': {'color': 'orange'}}
layout['yaxis2'] = {'title': 'Total Gen', 'side': 'left', 'overlaying': 'y', 'anchor': 'free', 'titlefont': {'color': 'red'}, 'tickfont': {'color': 'red'}}
layout['yaxis3'] = {'title': 'Frequency', 'side': 'right', 'overlaying': 'y', 'anchor': 'x', 'titlefont': {'color': 'purple'}, 'tickfont': {'color': 'purple'}}
    
pio.show({'data': traces, 'layout': layout})

Graph:

Given the nature of these traces, they overlay each other heavily, which could make graph interpretation difficult.

A couple of options are available:

• Change the range parameter for each y-axis so the axis only occupies a portion of the graph. For example, if a dataset ranges from 0-5, set the corresponding yaxis range parameter to [-15, 5], which will push that trace near the top of the graph.

• Consider using subplots, where like-traces can be grouped ... or each trace can have it's own graph. Here are Plotly's docs on subplots.

Comments (TL;DR):

The example code shown here uses the lower-level Plotly API, rather than a convenience wrapper such as graph_objects or express. The reason is that I (personally) feel it's helpful to users to show what is occurring 'under the hood', rather than masking the underlying code logic with a convenience wrapper.

This way, when the user needs to modify a finer detail of the graph, they will have a better understanding of the lists and dicts which Plotly is constructing for the underlying graphing engine (orca).

This is my function to plot any dataframe with index as x in the x axis. Should support any size of dataframes

def plotly_multi(data):
    if data.shape[1]>2:
        fig = go.Figure()
        fig.add_trace(
            go.Scatter(x=data.index, y=data.iloc[:, 0], name=data.columns[0]))
    
        fig.update_layout(
            xaxis=dict(domain=[0.1, 0.9]),
            yaxis=dict(title=data.columns[0]),
            yaxis2=dict(title=data.columns[1], anchor="x", overlaying="y", side="right"))
    
        for i, col in enumerate(data.columns[1:], 1):
            fig.add_trace(
                go.Scatter(x=data.index,y=data[col],name=col,yaxis=f"y{i+1}"))
    
        for i, col in enumerate(data.columns[2:], 2):
            axis = f"yaxis{i+1}"
    
            if i%2 == 0:
                side = "left"
                position = (i-1)*0.05
            else:
                side = "right"
                position = 1 - (i-2)*0.05
    
            axis_value = dict(
                title=col,
                anchor="free",
                overlaying="y",
                side=side,
                position=position)
            exec(f"fig.update_layout({axis} = axis_value)")
    if data.shape[1]==2:
        fig = make_subplots(specs=[[{"secondary_y": True}]])
        # Add traces
        fig.add_trace(
            go.Scatter(x=data.index, y=data.iloc[:, 0], name=data.columns[0]),
            secondary_y=False,)
        fig.add_trace(
            go.Scatter(x=data.index, y=data.iloc[:, 1], name=data.columns[1]),
            secondary_y=True,)
        # Set x-axis title
        fig.update_xaxes(title_text="Date")
        # Set y-axes titles
        fig.update_yaxes(title_text=data.columns[0], secondary_y=False)
        fig.update_yaxes(title_text=data.columns[0], secondary_y=True)
    if data.shape[1] == 1:
        fig = px.line(data.reset_index(), x = data.index.name, y = data.columns)
    
    fig.update_layout(
    title_text="Data",
    width=800,)
    
    fig.show()