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I would like to display all the results of Pyomo variables in a pandas dataframe. I had a look at this question Pyomo: Looping Over A Variable Method and tried to adjust it to my case without success. I always get error messages. Here is a part of my code:

model.set_timeslots = pyo.RangeSet(1, 288)
iterables = list (range (1, 288))
...
...
...
for v in model.component_objects(pyo.Var, active=True):
    for index in v:
        print(index, ': ', pyo.value(v[index]))

DF = pd.DataFrame(index=iterables)
for v in model.component_objects(pyo.Var, active=True):
    for index in v:
        DF.at[index, 'val'] = pyo.value(v[index])

So I would like to print each value of the variables for all 288 set values for the set model.set_timeslots. Further, I also have some variables that do not depend on a set (for example objective variables). I would also like them to be displayed in a pandas dataframe. Do you know how I can do that? I'd appreciate every comment and would be quite thankful for your help.

Reminder: Does nobody have an idea how I can do that?

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  • $\begingroup$ Would you try using this or this as offered by Pyomo? I hope they will be helpful. :) $\endgroup$
    – A.Omidi
    Commented Apr 20, 2021 at 10:40
  • $\begingroup$ Thanks for your comment A.Omidi. So shall I not ask questions about Pyomo in the Operations Research channel? I have seen quite many questions about Pyomo here. $\endgroup$
    – PeterBe
    Commented Apr 20, 2021 at 11:51
  • $\begingroup$ OR.SE is an optimization forum and actually, you can ask your related questions here. What I mentioned is two useful links offered by Pyomo developers in its host. You might get the answer to your technical questions there a bit quickly 😉 $\endgroup$
    – A.Omidi
    Commented Apr 20, 2021 at 19:31

1 Answer 1

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I don't know your entire code or the errors you get, but the general way is

optimal_values = [value(model.x[key]) for key in model.x]
df = pd.DataFrame(optimal_values)

where

model.x

is your target variable that is optimized.

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  • $\begingroup$ Thanks Steven for your answer. Unfortunately I get an error message when using your suggested code optimal_values = [value(model.variable_heatGenerationCoefficient_SpaceHeating[key]) for key in model.variable_heatGenerationCoefficient_SpaceHeating] df = pd.DataFrame(model.variable_heatGenerationCoefficient_SpaceHeating) stating "NameError: name 'value' is not defined". $\endgroup$
    – PeterBe
    Commented Apr 21, 2021 at 9:32
  • $\begingroup$ Further, I have quite many variables in my model (about 30). Is there no way how I can just get the values for all of them together e.g. via a loop? With your approach I would have to specify this for each of the 30 variables which is quite time consuming $\endgroup$
    – PeterBe
    Commented Apr 21, 2021 at 9:33
  • $\begingroup$ your second question: yes ofc, you can put all the variables in a list and then loop over the list (e.g. for model in model_list). I don't get why you get that name error (has something to do with your variable), maybe it's good to share you entire code or at least the crucial parts. $\endgroup$
    – Steven01123581321
    Commented Apr 21, 2021 at 9:40
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    $\begingroup$ I don't know what they mean with that error, but the part "for model.model_item in outputVariablesList" should be "for model_item in outputVariablesList" $\endgroup$
    – Steven01123581321
    Commented Apr 22, 2021 at 7:35
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    $\begingroup$ Thanks a lot Steven for your tremendous help and effort. It helped a lot. I upvoted and accepted your answer $\endgroup$
    – PeterBe
    Commented Apr 22, 2021 at 15:53

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