Loading data from .csv file into new variables

Question

Hello,
I have an exercise to load data from .csv file and count NPV for these values. I've done it, but I have a problem with loading seperate values into my NPV.

Here's my code:

__________________________________________________

from pandas import read_csv
from numpy import npv

def maxnpv():
if (npvA > npvB) and (npvA > npvC):
print("Most profitable is A.")
elif (npvB > npvA) and (npvB > npvC):
print("Most profitable is B.")
else:
print("Most profitable is C.")

fund = read_csv("inwestycje.csv", delimiter=',')
funds = [tuple(x) for x in fund.values]
project1 = tuple(funds[0])
project2 = tuple(funds[1])
project3 = tuple(funds[2])
npvA = npv(project1[1], [project1[2], project1[3], project1[4], project1[5], project1[6], project1[7], project1[8]])
npvB = npv(project2[1], [project2[2], project2[3], project2[4], project2[5], project2[6], project2[7], project2[8]])
npvC = npv(project3[1], [project3[2], project3[3], project3[4], project3[5], project3[6], project3[7], project3[8]])

print("NPV for project 'A': PLN {:,}".format(round(npvA, 2)))
print("NPV for project 'B': PLN {:,}".format(round(npvB, 2)))
print("NPV for project'C': PLN {:,}".format(round(npvC, 2)))

maxnpv()

__________________________________________________
And this is how the .csv file looks like:
https://i.imgur.com/B3uyLKz.jpg
__________________________________________________

As you can see, I loaded the values manually into "npv", but I want to make it automatic, so when the file doesn't consist 5 values, it should count it anyway with given amount.

How can I do it? Any ideas?
Thanks!

Answer 1

You can shorten it this way:

npvA = npv(project1[1], project1[2:])
npvB = npv(project2[1], project2[2:])
npvC = npv(project3[1], project3[2:])

Here is version for read n projects, except maxnpv()
(executable online)
https://onlinegdb.com/Sk6Lf6GxN

or on sololearn storage
https://code.sololearn.com/cyjIS6nRGtve/#py

Answer 2

Use python's for-loop shorthand:
https://code.sololearn.com/cpwVcF0Mr078/#py
Hope this helps.