how to stop interpolating the values that are missing in plotly?

Question

So I created the area plot of my data in plotly. My data has the whole year of the time block and the data which we have in the table is only for 84 days( 7 days per month), so it's like for the rest of the days we don't have the data(not zero, it's missing). So when I plot the area graph for this data its not showing 0 for the missing values in the rest of the days. for example:

You can see in the graph that the straight lines are actually the rest of the days where the data is missing and the clustered lines are the actual data that we have in the table. So is there a way so that we can tell the plotly that don't interpolate the values for the missing data or something like that or may be we can put zero in place of missing data? My code for this graph is:

import pandas as pd
import plotly.graph_objs as go
import plotly.offline as pyo
from plotly.subplots import make_subplots
import xlwings as xw
import logging
import glob


year = 2025
case = 'MNRE'
path1 = glob.glob("detailed output/"+str(year)+"/"+str(case)+"/with storage/[a-z]*.xlsx")
path2 = glob.glob("detailed output/"+str(year)+"/"+str(case)+"/without storage/[a-z]*.xlsx")

#Reading the data
app = xw.App(visible=False)
try:
    wb1 = app.books.open(path1[0])
    sheet = wb1.sheets['Fuel Wise Chart']
    dateWithStorage = sheet.range('A2:A8065').value
    coalWithStorage = sheet.range('D2:D8065').value
    nuclearWithStorage = sheet.range('E2:E8065').value
    gasWithStorage = sheet.range('F2:F8065').value
    bagasseWithStorage = sheet.range('G2:G8065').value
    hydroWithStorage = sheet.range('H2:H8065').value
    windWithStorage = sheet.range('I2:I8065').value
    solarWithStorage = sheet.range('J2:J8065').value
    bessCharging = sheet.range('L2:L8065').value
    bessDischarging = sheet.range('M2:M8065').value

    importSheet = wb1.sheets['Fuelwise Dispatch']
    importWithStorage = importSheet.range('CF2:CF8065').value

    wb2 = app.books.open(path2[0])
    sheet = wb2.sheets['Fuel Wise Chart']
    dateWithoutStorage = sheet.range('A2:A8065').value
    coalWithoutStorage = sheet.range('D2:D8065').value
    nuclearWithoutStorage = sheet.range('E2:E8065').value
    gasWithoutStorage = sheet.range('F2:F8065').value
    bagasseWithoutStorage = sheet.range('G2:G8065').value
    hydroWithoutStorage = sheet.range('H2:H8065').value
    windWithoutStorage = sheet.range('I2:I8065').value
    solarWithoutStorage = sheet.range('J2:J8065').value

    importSheet = wb2.sheets['Fuelwise Dispatch']
    importWithoutStorage = importSheet.range('CF2:CF8065').value

except Exception as e:
    logging.exception("Something awful happened!")
    print(e)
finally:
    app.quit()
    app.kill()
#Creating the area plot for with and without storage cases
fig = make_subplots(rows=2, cols=1, subplot_titles=("<b>Without Storage(With min run constraints relaxed for old plants)</b>", "<b>With Storage</b>"), shared_xaxes=True,
                    vertical_spacing = 0.06, y_title='<b>Fuel Wise Dispatch</b>')

trace1 = go.Scatter({'x': dateWithStorage,'y': coalWithStorage, 'name': 'Coal', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(71, 69, 69)'), 'stackgroup': 'one'})
trace2 = go.Scatter({'x': dateWithStorage,'y': nuclearWithStorage, 'name': 'Nuclear', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(255, 0, 0)'), 'stackgroup': 'one'})
trace3 = go.Scatter({'x': dateWithStorage,'y': gasWithStorage, 'name': 'Gas', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(0, 235, 227)'), 'stackgroup': 'one'})
trace4 = go.Scatter({'x': dateWithStorage,'y': bagasseWithStorage, 'name': 'Bagasse', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(154, 3, 255)'), 'stackgroup': 'one'})
trace5 = go.Scatter({'x': dateWithStorage,'y': hydroWithStorage, 'name': 'Hydro', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(0, 145, 255)'), 'stackgroup': 'one'})
trace6 = go.Scatter({'x': dateWithStorage,'y': windWithStorage, 'name': 'Wind', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(5, 252, 14)'), 'stackgroup': 'one'})
trace7 = go.Scatter({'x': dateWithStorage,'y': solarWithStorage, 'name': 'Solar', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(246, 255, 0)'), 'stackgroup': 'one'})
trace8 = go.Scatter({'x': dateWithStorage,'y': bessCharging, 'name': 'BESS Charging', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(145, 77, 4)'), 'stackgroup': 'one'})
trace9 = go.Scatter({'x': dateWithStorage,'y': bessDischarging, 'name': 'BESS Discharging', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(21, 102, 24)'), 'stackgroup': 'one'})
trace10 = go.Scatter({'x': dateWithStorage,'y': importWithStorage, 'name': 'Import', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(255, 161, 220)'), 'stackgroup': 'one'})

trace11 = go.Scatter({'x': dateWithStorage,'y': coalWithoutStorage, 'name': 'Coal', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(71, 69, 69)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace12 = go.Scatter({'x': dateWithStorage,'y': nuclearWithoutStorage, 'name': 'Nuclear', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(255, 0, 0)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace13 = go.Scatter({'x': dateWithStorage,'y': gasWithoutStorage, 'name': 'Gas','mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(0, 235, 227)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace14 = go.Scatter({'x': dateWithStorage,'y': bagasseWithoutStorage, 'name': 'Bagasse','mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(154, 3, 255)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace15 = go.Scatter({'x': dateWithStorage,'y': hydroWithoutStorage, 'name': 'Hydro','mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(0, 145, 255)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace16 = go.Scatter({'x': dateWithStorage,'y': windWithoutStorage, 'name': 'wind','mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(5, 252, 14)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace17 = go.Scatter({'x': dateWithStorage,'y': solarWithoutStorage, 'name': 'solar','mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(246, 255, 0)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
trace18 = go.Scatter({'x': dateWithStorage,'y': importWithoutStorage, 'name': 'Import', 'mode':'lines', 'line' : dict(width = 0.5, color = 'rgb(255, 161, 220)'), 'stackgroup': 'one', 'xaxis': 'x', 'showlegend': False})
# trace2 = go.Scatter({'x': dateWithStorage,'y': bessCharging, 'name': 'BESS Charging', 'mode':'lines', 'line' : dict(width = 0.5, color = 'brown'), 'stackgroup': 'one'})
# trace2 = go.Scatter({'x': dateWithStorage,'y': bessDischarging, 'name': 'BESS Discharging', 'mode':'lines', 'line' : dict(width = 0.5, color = 'orange'), 'stackgroup': 'one'})

fig.add_trace(trace1, 2, 1)
fig.add_trace(trace2, 2, 1)
fig.add_trace(trace3, 2, 1)
fig.add_trace(trace4, 2, 1)
fig.add_trace(trace5, 2, 1)
fig.add_trace(trace6, 2, 1)
fig.add_trace(trace7, 2, 1)
fig.add_trace(trace8, 2, 1)
fig.add_trace(trace9, 2, 1)
fig.add_trace(trace10, 2, 1)

fig.add_trace(trace11, 1, 1)
fig.add_trace(trace12, 1, 1)
fig.add_trace(trace13, 1, 1)
fig.add_trace(trace14, 1, 1)
fig.add_trace(trace15, 1, 1)
fig.add_trace(trace16, 1, 1)
fig.add_trace(trace17, 1, 1)
fig.add_trace(trace18, 1, 1)

fig.update_layout(title_text="<b>"+str(year)+' '+str(case)+" Scenario</b>",legend = dict(
    font=dict(
        family="Arial",
        size = 9
    )
))

# fig = go.Figure({'data': trace2}) #, 'layout': layout})
# fig.show()

pyo.plot(fig, filename= str(year)+' '+str(case)+' Plot with updated start up cost.html')

Answer 1

I know this question is old but since it is the first answer on duckduckgo when looking for the topic I think it is worth adding an answer. the behaviour of stackgaps is defined in the respective option. It is described as follows:

stackgaps – Only relevant when stackgroup is used, and only the first stackgaps found in the stackgroup will be used - including if visible is “legendonly” but not if it is false. Determines how we handle locations at which other traces in this group have data but this one does not. With infer zero we insert a zero at these locations. With “interpolate” we linearly interpolate between existing values, and extrapolate a constant beyond the existing values.

https://plotly.com/python-api-reference/generated/plotly.graph_objects.Scatter.html

If you set stackgaps="interpolate" your plot should look as expected.