Python2019/labs03/tmp.py
2019-02-09 08:54:14 +01:00

34 lines
746 B
Python

#!/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))