Matplotlib，从三个不等长的数组创建堆叠直方图 [英] Matplotlib, creating stacked histogram from three unequal length arrays

问题描述

我想创建一个堆叠的直方图.如果我有一个由三个等长数据集组成的二维数组，这很简单.下面的代码和图像:

将 numpy 导入为 np从 matplotlib 导入 pyplot 作为 plt#创建包含1,000个样本的3个数据集亩，西格玛 = 200, 25x = mu + sigma*np.random.randn(1000,3)#堆叠数据plt.figure()n，垃圾箱，补丁= plt.hist(x，30，堆叠=真，密度=真)plt.show()

但是，如果我尝试使用具有不同长度的三个数据集的相似代码，结果将是一个直方图覆盖了另一个.有什么方法可以处理混合长度数据集的堆叠直方图?

  ##接上###现在作为三个独立的数组x1 = mu + sigma*np.random.randn(990,1)x2 = mu + sigma * np.random.randn(980,1)x3 = mu + sigma*np.random.randn(1000,1)#堆叠数据plt.figure()plt.hist(x1，bins，stacked=True，密度=True)plt.hist(x2，bins，stacked=True，密度=True)plt.hist(x3，装箱，堆叠=真，密度=真)plt.show()

解决方案

嗯，这很简单.我只需要将三个数组放在一个列表中.

##接上###现在作为三个独立的数组x1 = mu + sigma * np.random.randn(990,1)x2 = mu + sigma * np.random.randn(980,1)x3 = mu + sigma * np.random.randn(1000,1)#堆叠数据plt.figure()plt.hist([x1,x2,x3], bins,stacked=True, density=True)plt.show()

I'd like to create a stacked histogram. If I have a single 2-D array, made of three equal length data sets, this is simple. Code and image below:

import numpy as np
from matplotlib import pyplot as plt

# create 3 data sets with 1,000 samples
mu, sigma = 200, 25
x = mu + sigma*np.random.randn(1000,3)

#Stack the data
plt.figure()
n, bins, patches = plt.hist(x, 30, stacked=True, density = True)
plt.show()

However, if I try similar code with three data sets of a different length the results are that one histogram covers up another. Is there any way I can do the stacked histogram with mixed length data sets?

##Continued from above
###Now as three separate arrays
x1 = mu + sigma*np.random.randn(990,1)
x2 = mu + sigma*np.random.randn(980,1)
x3 = mu + sigma*np.random.randn(1000,1)

#Stack the data
plt.figure()
plt.hist(x1, bins, stacked=True, density = True)
plt.hist(x2, bins, stacked=True, density = True)
plt.hist(x3, bins, stacked=True, density = True)
plt.show()

解决方案

Well, this is simple. I just need to put the three arrays in a list.

##Continued from above
###Now as three separate arrays
x1 = mu + sigma*np.random.randn(990,1)
x2 = mu + sigma*np.random.randn(980,1)
x3 = mu + sigma*np.random.randn(1000,1)

#Stack the data
plt.figure()
plt.hist([x1,x2,x3], bins, stacked=True, density=True)
plt.show()

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