Is there a way to set a custom baseline for a stacked area chart in Plotly?

Question

For context, what I'm trying to do is make an emission abatement chart that has the abated emissions being subtracted from the baseline. Mathematically, this is the same as adding the the abatement to the residual emission line:

Residual = Baseline - Abated

The expected results should look something like this:
Desired structure of stacked area chart:

I've currently got the stacked area chart to look like this:

As you can see, the way that the structure of stacked area chart is that the stacking starts at zero, however, I'm trying to get the stacking to either be added to the residual (red) line, or to be subtracted from the baseline (black).

I would do this in excel by just defining a blank area as the first stacked item, equal the residual line, so that the stacking occurs ontop of that. However, I'm not sure if there is a pythonic way to do this in plotly, while mainting the structure and interactivity of the chart.

The shaping of the pandas dataframes is pretty simple, just a randomly generated series of abatement values for each of the subcategories I've set up, that are then grouped to form the baseline and the residual forecasts:

scenario = 'High'

# The baseline data as a line
baseline_line = baselines.loc[baselines['Scenario']==scenario].groupby(['Year']).sum()

# The abatement and residual data
df2 = deepcopy(abatement).drop(columns=['tCO2e'])
df2['Baseline'] = baselines['tCO2e']
df2['Abatement'] = abatement['tCO2e']
df2 = df2.fillna(0)
df2['Residual'] = df2['Baseline'] - df2['Abatement']
df2 = df2.loc[abatement['Scenario']==scenario]
display(df2)

# The residual forecast as a line
emissions_lines = df2.loc[df2['Scenario']==scenario].groupby(['Year']).sum()

The charting is pretty simple as well, using the plotly express functionality:

# Just plotting

fig = px.area(df2,
             x = 'Year',
             y = 'Abatement',
             color = 'Site',
             line_group = 'Fuel_type'
             )

fig2 = px.line(emissions_lines,
             x = emissions_lines.index,
             y = 'Baseline',
             color_discrete_sequence = ['black'])

fig3 = px.line(emissions_lines,
             x = emissions_lines.index,
             y = 'Residual',
             color_discrete_sequence = ['red'])

fig.add_trace(
    fig2.data[0],
)

fig.add_trace(
    fig3.data[0],
)

fig.show()

To summarise, I wish to have the Plotly stacked area chart be 'elevated' so that it fits between the residual and baseline forecasts.

NOTE: I've used the term 'baseline' with two meanings here. One specific to my example, and one generic to stacked area chart (in the title). The first usage, in the title, is meant to be the series for which the stacked area chart starts. Currently, this series is just the x-axis, or zero, I'm wishing to have this customised so that I can define a series (in this example, the red residual line) that the stacking can start from. The second usage of the term 'baseline' refers to the 'baseline forecast', or BAU.

Answer 1

I think I've found a workaround, it is not ideal, but is similar to the approach I have taken in excel. I've ultimately added the 'residual' emissions in the same structure as the categories and concatenated it at the start of the DataFrame, so it bumps everything else up in between the residual and baseline forecasts.

Concatenation step:

# Me trying to make it cleanly at the residual line
df2b = deepcopy(emissions_lines)
df2b['Fuel_type'] = "Base"
df2b['Site'] = "Base"
df2b['Abatement'] = df2b['Residual']
df2c = pd.concat([df2b.reset_index(),df2],ignore_index=True)

Rejigged plotting step, with some recolouring/reformatting of the chart:

 # Just plotting
fig = px.area(df2c,
             x = 'Year',
             y = 'Abatement',
             color = 'Site',
             line_group = 'Fuel_type'
             )

# Making the baseline invisible and ignorable
fig.data[0].line.color='rgba(255, 255, 255,1)'
fig.data[0].showlegend = False

fig2 = px.line(emissions_lines,
             x = emissions_lines.index,
             y = 'Baseline',
             color_discrete_sequence = ['black'])

fig3 = px.line(emissions_lines,
             x = emissions_lines.index,
             y = 'Residual',
             color_discrete_sequence = ['red'])

fig.add_trace(
    fig2.data[0],
)

fig.add_trace(
    fig3.data[0],
)

fig.show()

Outcome:

I'm going to leave this unresolved, as I see this as not what I originally intended. It currently 'works', but this is not ideal and causes some issues with the interaction with the legend function in the Plotly object.