具有多个图例条目的Matplotlib直方图

Question

我有这个代码生成一个直方图，识别三种类型的字段; ＆＃34;低＆＃34;，＆＃34;中＆＃34; ，和＆＃34;高＆＃34;：

import pylab as plt
import pandas as pd


df = pd.read_csv('April2017NEW.csv', index_col =1)
df1 = df.loc['Output Energy, (Wh/h)']  # choose index value and Average
df1['Average'] = df1.mean(axis=1)

N, bins, patches = plt.hist(df1['Average'], 30)

cmap = plt.get_cmap('jet')
low = cmap(0.5)
medium =cmap(0.25)
high = cmap(0.8)


for i in range(0,4):
    patches[i].set_facecolor(low)
for i in range(4,11):
    patches[i].set_facecolor(medium)
for i in range(11,30):
    patches[i].set_facecolor(high)

plt.xlabel("Watt Hours", fontsize=16)  
plt.ylabel("Households", fontsize=16)
plt.xticks(fontsize=14)  
plt.yticks(fontsize=14)
ax = plt.subplot(111)  
ax.spines["top"].set_visible(False)  
ax.spines["right"].set_visible(False)

plt.show()

产生这个：

如何在这里获得三种不同颜色的图例？

Answer 1

您需要自己创建图例。为此，创建一些未在图中显示的矩形（所谓的代理艺术家）。

#create legend
handles = [Rectangle((0,0),1,1,color=c,ec="k") for c in [low,medium, high]]
labels= ["low","medium", "high"]
plt.legend(handles, labels)

完整示例：

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Rectangle

data = np.random.rayleigh(size=1000)*35

N, bins, patches = plt.hist(data, 30, ec="k")

cmap = plt.get_cmap('jet')
low = cmap(0.5)
medium =cmap(0.25)
high = cmap(0.8)


for i in range(0,4):
    patches[i].set_facecolor(low)
for i in range(4,11):
    patches[i].set_facecolor(medium)
for i in range(11,30):
    patches[i].set_facecolor(high)

#create legend
handles = [Rectangle((0,0),1,1,color=c,ec="k") for c in [low,medium, high]]
labels= ["low","medium", "high"]
plt.legend(handles, labels)

plt.xlabel("Watt Hours", fontsize=16)  
plt.ylabel("Households", fontsize=16)
plt.xticks(fontsize=14)  
plt.yticks(fontsize=14)

plt.gca().spines["top"].set_visible(False)  
plt.gca().spines["right"].set_visible(False)

plt.show()

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Answer 2

根据我的说法，您只需要在hist函数中将所需的标签作为参数传递，例如

plt.hist(x, bins=20, alpha=0.5, label='my label')

另请参见示例https://matplotlib.org/examples/statistics/histogram_demo_multihist.html