我需要重新排列图例中的项，但我认为我不应该这样做。 我尝试了：
from pylab import *
clf()
ax=gca()
ht=ax.add_patch(Rectangle((1,1),1,1,color='r',label='Top',alpha=.1))
h1=ax.bar(1,2,label='Middle')
hb=ax.add_patch(Rectangle((1,1),1,1,color='k',label='Bottom',alpha=.11))
legend()
show()
如何正确排列顺序？难道不是由创建顺序决定的吗？因为我最终得到了下面的顺序：底部在中间之上。
更新：可以使用以下代码强制排序。我认为这可能是最简单的方法，但看起来很笨拙。问题是什么决定了原始顺序呢？
hh=[ht,h1,hb]
legend([ht,h1.patches[0],hb],[H.get_label() for H in hh])
在其他答案的基础上稍作变化。列表order的长度应与图例项的数量相同，并手动指定新的顺序。
handles, labels = plt.gca().get_legend_handles_labels()
order = [0,2,1]
plt.legend([handles[idx] for idx in order],[labels[idx] for idx in order])
plt.axvline() 的调用的图例。当我调用 plt.legend() 时，垂直线在图例中正确显示，但是当我调用 plt.gca().get_legend_handles_labels() 时，它的句柄没有被包含进去。 :/ - aaronsnoswellax.plot(..., label='label1')
ax.plot(..., label='label2')
接下来是主要部分：
handles, labels = ax.get_legend_handles_labels()
# sort both labels and handles by labels
labels, handles = zip(*sorted(zip(labels, handles), key=lambda t: t[0]))
ax.legend(handles, labels)
这只是从http://matplotlib.org/users/legend_guide.html列出的代码进行简单改编。
ax.legend(*zip(*sorted(zip(*ax.get_legend_handles_labels()), key = lambda s: [int(t) if t.isdigit() else t.lower() for t in re.split('(\d+)', s[1])]))))。 - Caesar[235-242]行之间。您可以简单地收集每条绘制线的句柄，然后按照自己的喜好重新排序。供以后参考，这段简单的代码可以有效地更改线条顺序：fig,ax=plt.subplots();h1,=ax.plot([1,2,3],label='tag1');h2,=ax.plot([1,2,3],label='tag2');ax.legend(handles=[h2,h1]);plt.show() - C-3POorder）进行排序或部分排序。因此，您可以像这样使用它：reorderLegend(ax,['Top', 'Middle', 'Bottom'])
详情如下。
# Returns tuple of handles, labels for axis ax, after reordering them to conform to the label order `order`, and if unique is True, after removing entries with duplicate labels.
def reorderLegend(ax=None,order=None,unique=False):
if ax is None: ax=plt.gca()
handles, labels = ax.get_legend_handles_labels()
labels, handles = zip(*sorted(zip(labels, handles), key=lambda t: t[0])) # sort both labels and handles by labels
if order is not None: # Sort according to a given list (not necessarily complete)
keys=dict(zip(order,range(len(order))))
labels, handles = zip(*sorted(zip(labels, handles), key=lambda t,keys=keys: keys.get(t[0],np.inf)))
if unique: labels, handles= zip(*unique_everseen(zip(labels,handles), key = labels)) # Keep only the first of each handle
ax.legend(handles, labels)
return(handles, labels)
def unique_everseen(seq, key=None):
seen = set()
seen_add = seen.add
return [x for x,k in zip(seq,key) if not (k in seen or seen_add(k))]
更新后的函数在cpblUtilities.mathgraph中，位于https://gitlab.com/cpbl/cpblUtilities/blob/master/mathgraph.py。
使用方法如下：
fig, ax = plt.subplots(1)
ax.add_patch(Rectangle((1,1),1,1,color='r',label='Top',alpha=.1))
ax.bar(1,2,label='Middle')
ax.add_patch(Rectangle((.8,.5),1,1,color='k',label='Bottom',alpha=.1))
legend()
reorderLegend(ax,['Top', 'Middle', 'Bottom'])
show()
unique参数可以确保删除具有相同标签的重复绘图对象。
借鉴 Ian Hincks 的 答案，可以使用嵌套列表推导式在一行中更改图例元素的顺序。这样可以避免命名中间变量并减少代码重复。
plt.legend(*(
[ x[i] for i in [2,1,0] ]
for x in plt.gca().get_legend_handles_labels()
), handletextpad=0.75, loc='best')
我在结尾加入了一些额外的参数，以说明plt.legend()函数不需要分别调用来格式化和排序元素。
handles,labels = ax.get_legend_handles_labels()
sorted_legends= [x for _,x in sorted(zip(k,labels),reverse=True)]
#sort the labels based on the list k
#reverse=True sorts it in descending order
sorted_handles=[x for _,x in sorted(zip(k,handles),reverse=True)]
#to sort the colored handles
ax.legend(sorted_handles,sorted_legends,bbox_to_anchor=(1,0.5), loc='center left')
#display the legend on the side of your plot.
例子：
from matplotlib import pyplot as plt
import numpy as np
rollno=np.arange(1,11)
marks_math=np.random.randint(30,100,10)
marks_science=np.random.randint(30,100,10)
marks_english=np.random.randint(30,100,10)
print("Roll No. of the students: ",rollno)
print("Marks in Math: ",marks_math)
print("Marks in Science: ",marks_science)
print("Marks in English: ",marks_english)
average=[np.average(marks_math),np.average(marks_science),np.average(marks_english)] #storing the average of each subject in a list
fig1=plt.figure()
ax=fig1.add_subplot(1,1,1)
ax.set_xlabel("Roll No.")
ax.set_ylabel("Marks")
ax.plot(rollno,marks_math,c="red",label="marks in math, Mean="+str(average[0]))
ax.plot(rollno,marks_science,c="green",label="marks in science, Mean="+str(average[1]))
ax.plot(rollno,marks_english,c="blue",label="marks in english, Mean="+str(average[2]))
#ax.legend() # This would display the legend with red color first, green second and the blue at last
#but we want to sort the legend based on the average marks which must order the labels based on average sorted in decending order
handles,labels=ax.get_legend_handles_labels()
sorted_legends= [x for _,x in sorted(zip(average,labels),reverse=True)] #sort the labels based on the average which is on a list
sorted_handles=[x for _,x in sorted(zip(average,handles),reverse=True)] #sort the handles based on the average which is on a list
ax.legend(sorted_handles,sorted_legends,bbox_to_anchor=(1,0.5), loc='center left') #display the handles and the labels on the side
plt.show()
plt.close()
对于一个具有以下数值的运行：
Roll No. of the students: [ 1 2 3 4 5 6 7 8 9 10]
Marks in Math: [66 46 44 70 37 72 93 32 81 84]
Marks in Science: [71 99 99 40 59 80 72 98 91 81]
Marks in English: [46 64 74 33 86 49 84 92 67 35]
The average in each subject [62.5, 79.0, 63.0]
我在一个图中有几个主题相同的情节。当我尝试上面基于更改标签的答案时，我发现并排的情节会以不同的颜色显示相同的标签。
因此，对我有效的最简单的解决方案是在创建情节之前按所需的标签进行排序：
# Pandas adds the series in random order, we'll need to sort before plotting below...
pd.plotting.parallel_coordinates(
df.sort_values(by='tier_label'),
ax=ax,
class_column='tier_label',
alpha=0.5, color='#EDBB00 #004D98 #A50044'.split())
当然，这需要进行排序，因此您可以决定它是否适用于您的情况。此外，如果您需要标签文本与class_column不同，则可能需要添加更多代码。