Parses MN.csv and creates two files, after.csv and before.csv, which contain the number of floors and when the building was created for each building in the samples.

csvparser.py

import csv
import random
import math


def get_data(isAfter1950):
    with open("MN.csv") as csvfile:
        reader = csv.reader(csvfile)
        x = []
        for row in reader:
            if row[44] != "NumFloors" and float(row[44]) != 0 and row[60].isnumeric() and int(row[60]) != 0:
                if isAfter1950 and int(row[60]) >= 1950:
                    x.append((float(row[44]), row[60]))
                elif not isAfter1950 and int(row[60]) < 1950:
                    x.append((float(row[44]), row[60]))

        return x


def get_sample(x):
    ind = set()
    for i in range(40):
        gen = random.randint(1, len(x) - 1)
        while gen in ind:
            gen = random.randint(1, len(x) - 1)
        ind.add(gen)
    mean = 0
    for i in ind:
        mean += x[i][0]
    mean /= len(ind)
    diff = 0
    for j in ind:
        diff += (x[j][0] - mean) ** 2
    diff /= (len(ind) - 1)
    diff = math.sqrt(diff)
    return (mean, diff, ind)


x = get_data(True)
y = get_data(False)

m1, s1, i1 = get_sample(x)
m2, s2, i2 = get_sample(y)

value = (m1 - m2) / math.sqrt((s1 ** 2 / 40) + (s2 ** 2 / 40))

print(m1, s1)
print(m2, s2)
print(value)

newcsv = open("after.csv", "w")
for i in i1:
    newcsv.write(f"{x[i][0]}, {x[i][1]}\n")
newcsv.close()

newcsv = open("before.csv", "w")
for i in i2:
    newcsv.write(f"{y[i][0]}, {y[i][1]}\n")
newcsv.close()