import pandas as pd
import math

file_path = 'w3schools_Comedians (DT).csv'
data = pd.read_csv(file_path)


def Narmallashtirish(data):
    yosh = data['Age'].astype(int)
    min_yosh = yosh.min()
    max_yosh = yosh.max()
    narmal_yosh = round((yosh - min_yosh) / (max_yosh - min_yosh), 3)
    data['Narmal_yosh'] = narmal_yosh


def Max_abs_normal(data):
    Experience = data['Experience'].astype(int)
    max_exp = math.fabs(Experience.max())
    normal_exp = round(Experience / max_exp, 3)
    data['Nrl_ABS_Ex'] = normal_exp


def Standart_devation(a):
    z = sum(a) / len(a)
    b = []
    for i in range(0, len(a)):
        b.append((a[i] - z) ** 2)
    return math.pow(sum(b) / len(b), 0.5)


def Z_Score_narm(data):
    a = data['Rank'].astype(int)
    z_score = round((a - sum(a) / len(a)) / Standart_devation(a), 3)
    data['Z-Score-Rank'] = z_score


def my_function(data):
    yosh = data['Age'].astype(int)
    min_yosh = yosh.min()
    max_yosh = yosh.max()
    a, b = 3, 7
    narmal_yosh2 = round(a + (yosh - min_yosh) * (b - a) / (max_yosh - min_yosh), 3)
    data['Narmal_yosh2'] = narmal_yosh2


def for_print():
    Z_Score_narm(data)
    Max_abs_normal(data)
    Narmallashtirish(data)
    my_function(data)
    print(data[['Age', 'Experience', 'Rank', 'Narmal_yosh', 'Nrl_ABS_Ex', 'Z-Score-Rank', 'Narmal_yosh2']])


for_print()