from prettytable import PrettyTable

def get_size(statistic_series):
    '''
    Возвращает размер выборки
    '''
    n = 0
    for pair in statistic_series:
        n += pair[1]
    return n

def get_statistic_series_as_input_selection():
    '''
    Возвращает статистический ряд
    '''
    statistic_series = []
    print('Введите выборку: ')
    while True:
        try:
            xi = float(input('Введите число: '))

            updated = False
            for pair in statistic_series:
                if pair[0] == xi:
                    pair[1]+=1#update
                    updated = True

            if not updated:
                statistic_series.append([xi, 1])
        except Exception as err:
            break
    return sorted(statistic_series, key=lambda pair: pair[0])

def get_statistic_series():
    '''
    Возвращает статистический ряд
    '''
    statistic_series = []
    print('Ввод статистического ряда: ')
    i = 1
    while True:
        try:
            xi = float(input('Введите число x{}: '.format(i)))
            i += 1
            ni = int(input('Введите частоту появления: '))

            if ni <= 0:
                raise Exception()

            updated = False
            for pair in statistic_series:
                if pair[0] == xi:
                    pair[1]=ni#update
                    updated = True

            if not updated:
                statistic_series.append([xi, ni])
        except Exception as err:
            break
    return sorted(statistic_series, key=lambda pair: pair[0])

def put_emperical_function(statistic_series):
    '''
    Принимает отстортированный по значению список пар значение-частота появления
    Выводит эмпирическую функцию распредления по статистическому ряду
    '''
    n = get_size(statistic_series)#объем выборки

    size = len(statistic_series)

    min_pair = statistic_series[0]
    max_pair = statistic_series[size - 1]

    print('Эмпирическая функция распределения: ')
    print('F*(x)=0 при x<=' + str(min_pair[0]))

    last_pair=min_pair

    accumulator = min_pair[1]

    for i in range(1, size):
        prev_pair = statistic_series[i - 1]
        curr_pair = statistic_series[i]

        left_end = prev_pair[0]
        right_end = curr_pair[0]

        print('F*(x)={}/{} при {}<x<={}'.format(accumulator, n, left_end, right_end))
        accumulator += curr_pair[1]


    print('F*(x)=1 при x>' + str(max_pair[0]))

def get_medium(statistic_series):
    accumulator = 0
    n = get_size(statistic_series)
    for pair in statistic_series:
        xi = pair[0]
        ni = pair[1]
        accumulator += xi * ni
    return accumulator/n

def get_dispersion(statistic_series):
    '''
    Возвращает дисперсию выборки
    '''
    sum = 0
    n = get_size(statistic_series)
    medium = get_medium(statistic_series)
    for pair in statistic_series:
        xi = pair[0]
        sum += (xi - medium)**2
    return sum/n

def get_corrected_dispersion(statistic_series):
    '''
    Возвращает исправленную дисперсию
    '''
    n = get_size(statistic_series)
    dispersion = get_dispersion(statistic_series)
    return (n / (n-1)) * dispersion

def show_statistic_series(two_selections):
    print('Статистический ряд: ')
    table = PrettyTable(['i', 'Xi', 'Ni'])
    for i in range(len(two_selections)):
        curr_pair = two_selections[i]
        xi = curr_pair[0]
        ni = curr_pair[1]
        table.add_row([i+1, xi, ni])
    print(table)

statistic_series = get_statistic_series_as_input_selection()
show_statistic_series(statistic_series)
put_emperical_function(statistic_series)
medium = get_medium(statistic_series)
print('Выборочное среднее: ' + str(medium))
dispersion = get_dispersion(statistic_series)
print('Дисперсия: ' + str(dispersion))
corrected_dispersion = get_corrected_dispersion(statistic_series)
print('Исправленная дисперсия: ' + str(corrected_dispersion))