Python 用于条形图的matplotlib多重xticklabel

Python 用于条形图的matplotlib多重xticklabel,python,python-2.7,matplotlib,Python,Python 2.7,Matplotlib,我有一组如下所示的数据,是否可以用它们自己的索引来标记每个条形图?例如,对于第一组3个条形图,红色、绿色和蓝色条形图的xticklabel应分别为[data1a、data1b、data1c]。使用下面的代码,我只能使用“data1a”标记 d1label = ['data1a', 'data2a'] data1 = [204.24, 224.24] d2label = ['data1b', 'data2b'] data2 = [206.24, 226.24] d3label = ['data1c

我有一组如下所示的数据,是否可以用它们自己的索引来标记每个条形图?例如,对于第一组3个条形图,红色、绿色和蓝色条形图的xticklabel应分别为[data1a、data1b、data1c]。使用下面的代码,我只能使用“data1a”标记

d1label = ['data1a', 'data2a']
data1 = [204.24, 224.24]
d2label = ['data1b', 'data2b']
data2 = [206.24, 226.24]
d3label = ['data1c', 'data2c']
data3 = [208.24, 228.24]

def plot_tribar(logfile, ylabel, d1label, data1, d2label, data2, d3label, data3):
    fig, ax = plt.subplots()    
    ind = np.arange(len(data1))    
    width = 0.3       # the width of the bars

    rects1 = ax.bar(ind, data1, width, color='r', label='Bar1')
    rects2 = ax.bar(ind+width, data2, width, color='g', label='Bar2')
    rects3 = ax.bar(ind+(2*width), data3, width, color='b', label='Bar3')

    handles, labels = ax.get_legend_handles_labels()
    fontP = FontProperties()
    fontP.set_size('small')
    ax.legend(handles, labels, loc='best', prop=fontP)   

    ax.set_xticks(ind+width)  
    ax.set_xticklabels(d1label) 
    ax.set_ylabel(ylabel) 

    fig.autofmt_xdate()

    def autolabel(rects):        
        for rect in rects:
            height = rect.get_height()
            if height >= 1:
                ax.text(rect.get_x()+rect.get_width()/2., 1.01*height, '%d'%int(height), ha='center', va='bottom', fontsize=10)

    autolabel(rects1)
    autolabel(rects2)
    autolabel(rects3)

    plt.show()
这就是你想要的吗

from matplotlib import pyplot as plt
import numpy as np
d1label = ['data1a', 'data2a']
data1 = [204.24, 224.24]
d2label = ['data1b', 'data2b']
data2 = [206.24, 226.24]
d3label = ['data1c', 'data2c']
data3 = [208.24, 228.24]

width = 0.3

data = np.concatenate([data1, data2, data3])
labels = np.concatenate([d1label, d2label, d3label])
colors = np.repeat(["r", "g", "b"], [len(data1), len(data2), len(data3)])
idx = np.arange(len(data1))
x = np.concatenate([idx, idx+width, idx+width*2])
plt.bar(x, data, width=0.3, color=colors)
ax = plt.gca()
ax.set_xticks(x + width*0.5)
ax.set_xticklabels(labels);
情节: