forked from tdwojak/Python2019
34 lines
746 B
Python
34 lines
746 B
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import numpy as np
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with open("./dane.txt") as ff:
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x = [int(line.strip()) for line in ff]
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print(np.mean(x))
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print(np.var(x))
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print(min(x))
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print(max(x))
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x_scaled = [(i - min(x)) / (max(x) - min(x)) for i in x]
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print(min(x_scaled), max(x_scaled))
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def normalize(data):
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return [(i - np.mean(x)) / np.sqrt(np.var(x)) for i in data]
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normalized = normalize(x)
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print(np.mean(normalized), np.var(normalized))
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x_binned = [i // 10 for i in x]
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for begin in range(0, 1 + max(x_binned)):
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if begin == 0:
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print("[ ", 10 * begin, ", ", 10 * begin + 9, "]", "+" * x_binned.count(begin))
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else:
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print("[", 10 * begin, ",", 10 * begin + 9, "]", "+" * x_binned.count(begin))
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