Discover the power of Python tuples—a cornerstone of immutable, ordered collections. Learn about tuple packing and unpacking, and how tuples enhance data integrity and efficiency in Python programming.

import pandas as pd
import csv

def getMedian(lst):
    sorted_lst = sorted(lst)
    n = len(sorted_lst)
    if n % 2 == 0:
        middle1 = sorted_lst[n // 2 - 1]
        middle2 = sorted_lst[n // 2]
        median = (middle1 + middle2) / 2
    else:
        median = sorted_lst[n // 2]
    return median

ceditlist=[]
print(type(ceditlist))
with open("/Users/npblue/PycharmProjects/data/credit.csv", 'r') as file:
  csvreader = csv.reader(file, delimiter=',')
  count=0
  for row in csvreader:
      if count==0:
          count += 1
      else:

          ceditlist.append(row)

amountTuple=()
for row in ceditlist:
    amountTuple+=(float(row[7]),)

print(amountTuple)

print("Type  :",type(amountTuple))

print("min value :",min(amountTuple))

print("max value :",max(amountTuple))

print("mean value :",sum(amountTuple)//len(amountTuple))

print("median value :",getMedian(amountTuple))

#Mode: The most frequent number—that is, the number that occurs the highest number
# of times.
# mode we can not calculate using set because all element are unique
#print("mode value :",max(set(amountset), key=amountset.count))