Python PULP数组乘法约束

Question

I am trying to run an optimization problem, which i can't seem to solve. I am a rookie in Python.

I have a dataframe with 8760 numbers ( 0 - 1). I need to multiply each row in this array by a factor and then sum this array. This sum of this should equal x, 50,000 for example. A sample of my code is.

pp.prob = pp.LpProblem("P2g", pp.LpMinimize)
SolarCap = pp.LpVariable("SolarCap", lowBound=0)

pp.prob +=  SolarCap * 5

for i,j in enumerate(SolverWS['Solar']):
    x = j * SolarCap
    x = x + x 
    pp.prob += x == P2gprod

status = pp.prob.solve()

Answer 1

If I understood correctly you need to multiply a pandas dataframe consisting of n entries by the same factor per each row and then sum the resulting dataframe.

You could use the mul() method of Pandas Dataframes (documentation here )

As for summing the elements, all you have to do is call sum() on the dataframe .values property

Here's a simple example

import numpy as np
import pandas as pd
# Create a random dataframe of 10 columns and 876 rows with random float values between 0 and 1
df = pd.DataFrame(np.random.uniform(0,1,size=(876, 10)))
print(df)
print(df.values.sum())
other = 10
# See https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.multiply.html
df1 = df.mul(other)
# Alternatively, for just multiplying the whole dataframe
#df1 = df * 10
print(df1)
print(df1.values.sum())