利用python，使用直方图绘制累积分布图

最新推荐文章于 2024-07-09 15:47:58 发布

原创最新推荐文章于 2024-07-09 15:47:58 发布 · 3.5k 阅读

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#python #线性代数 #开发语言

本文介绍如何利用Python编程语言，结合统计方法，绘制累积分布直方图。通过实例详细解析步骤，包括数据处理、直方图绘制及累计分布计算，帮助读者掌握这一实用技能。

# -*- coding: utf-8 -*-
"""
Created on Tue Nov 16 20:38:41 2021

@author: Machi
"""
import numpy as np
import matplotlib.pyplot as plt

%config InlineBackend.figure_format = 'retina'
np.random.seed(190801)

mu = 200
sigma = 25
n_bins = 50
x = np.random.normal(mu, sigma, size=100)

fig, ax = plt.subplots(figsize=(8, 4))

# plot the cumulative histogram
n, bins, patches = ax.hist(x, n_bins, density=True, histtype='step',
                           cumulative=True, label='Empirical')

# Add a line showing the expected distribution.
y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *
     np.exp(-0.5 * (1 / sigma * (bins - mu))**2))
y = y.cumsum()
y /= y[-1]

ax.plot(bins, y, 'k--', linewidth=1.5, label='Theoretical')

# Overlay a reversed cumulative histogram.
ax.hist(x, bins=bins, density=True, histtype='step', cumulative=-1,
        label='Reversed emp.')

# tidy up the figure
ax.grid(True)
ax.legend(loc='right')
ax.set_title('Cumulative step histograms')
ax.set_xlabel('Annual rainfall (mm)')
ax.set_ylabel('Likelihood of occurrence')

plt.show()