#!/usr/bin/env python
# -*- coding: utf-8 -*-

import numpy as np

with open("./dane.txt") as ff:
    x = [int(line.strip()) for line in ff]

print(np.mean(x))
print(np.var(x))

print(min(x))
print(max(x))

x_scaled = [(i - min(x)) / (max(x) - min(x)) for i in x]
print(min(x_scaled), max(x_scaled))

def normalize(data):
    return [(i - np.mean(x)) / np.sqrt(np.var(x)) for i in data]

normalized = normalize(x)

print(np.mean(normalized), np.var(normalized))

x_binned = [i // 10 for i in x]


for begin in range(0, 1 + max(x_binned)):
    if begin  == 0:
        print("[ ", 10 * begin, ", ",  10 * begin + 9, "]", "+" * x_binned.count(begin))
    else:
        print("[", 10 * begin, ",",  10 * begin + 9, "]", "+" * x_binned.count(begin))