Question

我需要使用matplotlib创建堆积条形图。每个条形应该是我正在测量的参数的堆栈。但是，我希望它是交互式的或动态的，因此当我点击图例中的一个参数（A，B，C）时，它应该在堆栈的底部创建该参数，以便我们可以拥有根据我们选择的参数，更好地比较不同的候选人。

我从matplotlib的例子中获得灵感。这是我的代码

import numpy as np
import matplotlib.pyplot as plt

N = 10  #could change

plt.figure()

A   = np.array([70, 88, 78, 93, 99, 58, 89, 66, 77, 78])
B = np.array([73, 65, 78, 87, 97, 57, 77, 88, 69, 78])
C = np.array([66, 98, 88, 67, 99, 88, 62, 70, 90, 73])


ind = np.arange(N)    # the x locations for the groups
width = 0.35       # the width of the bars: can also be len(x) sequence

p1 = plt.bar(ind, A,width, color='r')
p2 = plt.bar(ind, B, width, color='y', bottom=A)
p3 = plt.bar(ind, C, width, color='b', bottom=A+B)


plt.ylabel('Scores')
plt.title('Index')

plt.xticks(ind+width/2., ('1', '2', '3', '4', '5', '6', '7', '8', '9', '10'))#dynamic - fed

plt.yticks(np.arange(0,300,10))
plt.legend( (p1[0], p2[0], p3[0]), ('A','B','C') )
plt.grid(True)


plt.show()

谢谢......我希望我足够清楚

Answer 1

7年后，但我想我会使用Python 3.6.0和Matplotlib 2.0.0为此提供解决方案

import numpy as np
import matplotlib.pyplot as plt

#Variables
bar_a = np.array([70, 88, 78, 93, 99, 58, 89, 66, 77, 78])
bar_b = np.array([73, 65, 78, 87, 97, 57, 77, 88, 69, 78])
bar_c = np.array([66, 98, 88, 67, 99, 88, 62, 70, 90, 73])
xloc = np.arange(len(bar_a)) #Get a count of postions in bar_a instead of declaring 10.
width = 0.5  # the width of the bars: can also be len(x) sequence

#Plotting
fig = plt.figure(figsize=(6,6))
p1 = plt.bar(xloc, bar_a, width, color='r', label='A')
p2 = plt.bar(xloc, bar_b, width, color='y', bottom=bar_a, label='B')
p3 = plt.bar(xloc, bar_c, width, color='b', bottom=bar_a+bar_b, label='C')

plt.xticks(xloc+width/2., (str(num+1) for num in xloc)) #dynamic instead of ('1', '2', '3', '4', '5', '6', '7', '8', '9', '10'))
plt.yticks(np.arange(0,300,10))
plt.ylabel('Scores')
plt.title('Index')
leg = plt.legend()
plt.grid(True)

#For setting and selecting legend items
barcontainers = [p1, p2, p3] #List of BarContainers
legendentry = [] #Mathing Lenged Entry to bar container

#Set pickers on the legend
for legenditem in leg.get_patches():
    legenditem.set_picker(5)
    legendentry.append(legenditem) #Append to legend entry to a list so we can get the index later

#Function to redraw on picking
def onpick(event):
    tempbarcontainers = barcontainers[:] #Make a copy of barcontainers. Used for re-ordering of bars
    selectedforbottom = legendentry.index(event.artist) #Index of selected artist

    #Use the index of the selected Legend entry as the index of the barcontainer list.
    bottombars = tempbarcontainers[selectedforbottom].patches #Bottom bar will be the one selected
    tempbarcontainers.pop(selectedforbottom) #Pop the selected artist from the list
    midbars = tempbarcontainers[0].patches #Mid bars is first of remaining bars
    topbars = tempbarcontainers[1].patches #Top bar is second of remaining bars

    for bottom, mid, top in zip(bottombars,midbars,topbars):
        bottom.set_y(0) #Set the bottom of each selected bar to 0
        mid.set_y(bottom.get_height()) #Set the bottom of the second bar to the top of bottom bar
        top.set_y(bottom.get_height() + mid.get_height()) #Set the bottom of third bar to the top of the sum of other bars

    fig.canvas.draw() #Redraw the canvas

fig.canvas.mpl_connect('pick_event', onpick)

plt.show()

使用MatplotLib python的交互式堆积条形图

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