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Thank you
Great example.. practical linear programming application
Thanks for sharing and in #Create optimization Function, the code should be modified as follows.
Create optimization Function
total_views = ' '
for rownum, row in data.iterrows():
for i, talk in enumerate(decision_variables):
if rownum == i:
formula = row['views'] * talk
total_views += formula
prob += total_views
print('Optimization function: ' + str(total_views))
Very nice code and idea. Thank you for sharing. I used pulp.LpAffineExpression and dictionaries to define the objective function and constraint equations, it worked well.
I should also mention that one would get a different list with and without rounding. I guess this is because of the rounding process.
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Great example.. practical linear programming application
Also, I second the pandas misspelling