blocks|key|225907|text|由于我在matplotlib中找不到内置的解决方案，所以我编写了自己的解决方案：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|225908|#!/usr/bin/env+python

from+matplotlib+import+pyplot+as+plt

def+mk_groups(data):
++++try:
++++++++newdata+=+data.items()
++++except:
++++++++return

++++thisgroup+=+[]
++++groups+=+[]
++++for+key,+value+in+newdata:
++++++++newgroups+=+mk_groups(value)
++++++++if+newgroups+is+None:
++++++++++++thisgroup.append((key,+value))
++++++++else:
++++++++++++thisgroup.append((key,+len(newgroups[-1])))
++++++++++++if+groups:
++++++++++++++++groups+=+[g+%2B+n+for+n,+g+in+zip(newgroups,+groups)]
++++++++++++else:
++++++++++++++++groups+=+newgroups
++++return+[thisgroup]+%2B+groups

def+add_line(ax,+xpos,+ypos):
++++line+=+plt.Line2D([xpos,+xpos],+[ypos+%2B+.1,+ypos],
++++++++++++++++++++++transform=ax.transAxes,+color='black')
++++line.set_clip_on(False)
++++ax.add_line(line)

def+label_group_bar(ax,+data):
++++groups+=+mk_groups(data)
++++xy+=+groups.pop()
++++x,+y+=+zip(*xy)
++++ly+=+len(y)
++++xticks+=+range(1,+ly+%2B+1)

++++ax.bar(xticks,+y,+align='center')
++++ax.set_xticks(xticks)
++++ax.set_xticklabels(x)
++++ax.set_xlim(.5,+ly+%2B+.5)
++++ax.yaxis.grid(True)

++++scale+=+1.+/+ly
++++for+pos+in+xrange(ly+%2B+1):++#+change+xrange+to+range+for+python3
++++++++add_line(ax,+pos+*+scale,+-.1)
++++ypos+=+-.2
++++while+groups:
++++++++group+=+groups.pop()
++++++++pos+=+0
++++++++for+label,+rpos+in+group:
++++++++++++lxpos+=+(pos+%2B+.5+*+rpos)+*+scale
++++++++++++ax.text(lxpos,+ypos,+label,+ha='center',+transform=ax.transAxes)
++++++++++++add_line(ax,+pos+*+scale,+ypos)
++++++++++++pos+%2B=+rpos
++++++++add_line(ax,+pos+*+scale,+ypos)
++++++++ypos+-=+.1

if+__name__+==+'__main__':
++++data+=+{'Room+A':
+++++++++++++++{'Shelf+1':
+++++++++++++++++++{'Milk':+10,
++++++++++++++++++++'Water':+20},
++++++++++++++++'Shelf+2':
+++++++++++++++++++{'Sugar':+5,
++++++++++++++++++++'Honey':+6}
+++++++++++++++},
++++++++++++'Room+B':
+++++++++++++++{'Shelf+1':
+++++++++++++++++++{'Wheat':+4,
++++++++++++++++++++'Corn':+7},
++++++++++++++++'Shelf+2':
+++++++++++++++++++{'Chicken':+2,
++++++++++++++++++++'Cow':+1}
+++++++++++++++}
+++++++++++}
++++fig+=+plt.figure()
++++ax+=+fig.add_subplot(1,1,1)
++++label_group_bar(ax,+data)
++++fig.subplots_adjust(bottom=0.3)
++++fig.savefig('label_group_bar_example.png')|code-block|syntax|javascript|225909|mk_groups函数接受字典(或任何带有items()方法的内容，如collections.OrderedDict)，并将其转换为数据格式，然后用于创建图表。它基本上是一个表单列表：|offset|length|style|CODE|225910|[+[(label,+bars_to_span),+...],+...,+[(tick_label,+bar_value),+...]+]|225911|add_line函数在子图中的指定位置(在轴坐标中)创建一条垂直线。|225912|label_group_bar函数获取一个字典，并在下面带有标签的子图中创建条形图。然后，该示例的结果看起来是like+this。|225913|更容易或更好的解决方案和建议仍然非常受欢迎。|225914|​|225915|📷|atomic|225916|225917|entityMap|0|LINK|mutability|MUTABLE|url|https://ask.qcloudimg.com/http-save/yehe-900000/3958674d527644f5d76a0447b2d9593e.png|1|IMAGE|IMMUTABLE|imageUrl|imageAlt^0|0|0|0|9|Z|N|0|0|0|8|0|0|F|1J|9|0|0|0|0|0|1|1|0|0^^$0|@$1|2|3|4|5|6|7|1D|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|1E|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|1F|8|@$I|1G|J|1H|K|L]|$I|1I|J|1J|K|L]]|9|@]|A|$]]|$1|M|3|N|5|D|7|1K|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|1L|8|@$I|1M|J|1N|K|L]]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1O|8|@$I|1P|J|1Q|K|L]]|9|@$I|1R|J|1S|1|1T]]|A|$]]|$1|S|3|T|5|6|7|1U|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1V|8|@]|9|@]|A|$]]|$1|W|3|X|5|Y|7|1W|8|@]|9|@$I|1X|J|1Y|1|1Z]]|A|$]]|$1|Z|3|V|5|6|7|20|8|@]|9|@]|A|$]]|$1|10|3|-4|5|6|7|21|8|@]|9|@]|A|$]]]|11|$12|$5|13|14|15|A|$16|17]]|18|$5|19|14|1A|A|$1B|17|1C|-4]]]]

Since I could not find a built-in solution for this in matplotlib, I coded my own:
<pre><code>#!/usr/bin/env python

from matplotlib import pyplot as plt

def mk_groups(data):
 try:
 newdata = data.items()
 except:
 return

 thisgroup = []
 groups = []
 for key, value in newdata:
 newgroups = mk_groups(value)
 if newgroups is None:
 thisgroup.append((key, value))
 else:
 thisgroup.append((key, len(newgroups[-1])))
 if groups:
 groups = [g + n for n, g in zip(newgroups, groups)]
 else:
 groups = newgroups
 return [thisgroup] + groups

def add_line(ax, xpos, ypos):
 line = plt.Line2D([xpos, xpos], [ypos + .1, ypos],
 transform=ax.transAxes, color='black')
 line.set_clip_on(False)
 ax.add_line(line)

def label_group_bar(ax, data):
 groups = mk_groups(data)
 xy = groups.pop()
 x, y = zip(*xy)
 ly = len(y)
 xticks = range(1, ly + 1)

 ax.bar(xticks, y, align='center')
 ax.set_xticks(xticks)
 ax.set_xticklabels(x)
 ax.set_xlim(.5, ly + .5)
 ax.yaxis.grid(True)

 scale = 1. / ly
 for pos in xrange(ly + 1): # change xrange to range for python3
 add_line(ax, pos * scale, -.1)
 ypos = -.2
 while groups:
 group = groups.pop()
 pos = 0
 for label, rpos in group:
 lxpos = (pos + .5 * rpos) * scale
 ax.text(lxpos, ypos, label, ha='center', transform=ax.transAxes)
 add_line(ax, pos * scale, ypos)
 pos += rpos
 add_line(ax, pos * scale, ypos)
 ypos -= .1

if __name__ == '__main__':
 data = {'Room A':
 {'Shelf 1':
 {'Milk': 10,
 'Water': 20},
 'Shelf 2':
 {'Sugar': 5,
 'Honey': 6}
 },
 'Room B':
 {'Shelf 1':
 {'Wheat': 4,
 'Corn': 7},
 'Shelf 2':
 {'Chicken': 2,
 'Cow': 1}
 }
 }
 fig = plt.figure()
 ax = fig.add_subplot(1,1,1)
 label_group_bar(ax, data)
 fig.subplots_adjust(bottom=0.3)
 fig.savefig('label_group_bar_example.png')
</code></pre>
The <code>mk_groups</code> function takes a dictionary (or anything with an items() method, like <code>collections.OrderedDict</code>) and converts it to a data format that is then used to create the chart. It is basically a list of the form:
<pre><code>[ [(label, bars_to_span), ...], ..., [(tick_label, bar_value), ...] ]
</code></pre>
The <code>add_line</code> function creates a vertical line in the subplot at the specified positions (in axes coordinates).
The <code>label_group_bar</code> function takes a dictionary and creates the bar chart in the subplot with the labels beneath. The result from the example then looks <a href="https://i.stack.imgur.com/Zt9YP.png" rel="nofollow noreferrer">like this</a>.
Easier or better solutions and suggestions are still very much appreciated.
<img src="https://i.stack.imgur.com/Zt9YP.png" alt="bar chart with groups" />

blocks|key|9417|text|我寻找这个解决方案已经有一段时间了。我对它进行了一些修改，以便与pandas数据表一起使用。只有公平地分享。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|9418|import+pandas+as+pd
import+numpy+as+np
from+matplotlib+import+pyplot+as+plt
from+itertools+import+groupby

def+test_table():
++++data_table+=+pd.DataFrame({'Room':['Room+A']*4+%2B+['Room+B']*4,
+++++++++++++++++++++++++++++++'Shelf':(['Shelf+1']*2+%2B+['Shelf+2']*2)*2,
+++++++++++++++++++++++++++++++'Staple':['Milk','Water','Sugar','Honey','Wheat','Corn','Chicken','Cow'],
+++++++++++++++++++++++++++++++'Quantity':[10,20,5,6,4,7,2,1],
+++++++++++++++++++++++++++++++'Ordered':np.random.randint(0,10,8)
+++++++++++++++++++++++++++++++})
++++return+data_table

def+add_line(ax,+xpos,+ypos):
++++line+=+plt.Line2D([xpos,+xpos],+[ypos+%2B+.1,+ypos],
++++++++++++++++++++++transform=ax.transAxes,+color='black')
++++line.set_clip_on(False)
++++ax.add_line(line)

def+label_len(my_index,level):
++++labels+=+my_index.get_level_values(level)
++++return+[(k,+sum(1+for+i+in+g))+for+k,g+in+groupby(labels)]
++++
def+label_group_bar_table(ax,+df):
++++ypos+=+-.1
++++scale+=+1./df.index.size
++++for+level+in+range(df.index.nlevels)[::-1]:
++++++++pos+=+0
++++++++for+label,+rpos+in+label_len(df.index,level):
++++++++++++lxpos+=+(pos+%2B+.5+*+rpos)*scale
++++++++++++ax.text(lxpos,+ypos,+label,+ha='center',+transform=ax.transAxes)
++++++++++++add_line(ax,+pos*scale,+ypos)
++++++++++++pos+%2B=+rpos
++++++++add_line(ax,+pos*scale+,+ypos)
++++++++ypos+-=+.1

df+=+test_table().groupby(['Room','Shelf','Staple']).sum()
fig+=+plt.figure()
ax+=+fig.add_subplot(111)
df.plot(kind='bar',stacked=True,ax=fig.gca())
#Below+3+lines+remove+default+labels
labels+=+[''+for+item+in+ax.get_xticklabels()]
ax.set_xticklabels(labels)
ax.set_xlabel('')
label_group_bar_table(ax,+df)
fig.subplots_adjust(bottom=.1*df.index.nlevels)
plt.show()|code-block|syntax|javascript|9419|​|9420|📷|atomic|offset|length|9421|9422|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/c98f9e3e63f065932bd9dbcb500d954e.png|imageAlt^0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|X|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|Y|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Z|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|10|8|@]|9|@$L|11|M|12|1|13]]|A|$]]|$1|N|3|H|5|6|7|14|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|15|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V|W|-4]]]]

I was looking for this solution for a while.
I modified it some to work with a pandas data table.
Only fair to share.
<pre><code>import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from itertools import groupby

def test_table():
 data_table = pd.DataFrame({'Room':['Room A']*4 + ['Room B']*4,
 'Shelf':(['Shelf 1']*2 + ['Shelf 2']*2)*2,
 'Staple':['Milk','Water','Sugar','Honey','Wheat','Corn','Chicken','Cow'],
 'Quantity':[10,20,5,6,4,7,2,1],
 'Ordered':np.random.randint(0,10,8)
 })
 return data_table

def add_line(ax, xpos, ypos):
 line = plt.Line2D([xpos, xpos], [ypos + .1, ypos],
 transform=ax.transAxes, color='black')
 line.set_clip_on(False)
 ax.add_line(line)

def label_len(my_index,level):
 labels = my_index.get_level_values(level)
 return [(k, sum(1 for i in g)) for k,g in groupby(labels)]
 
def label_group_bar_table(ax, df):
 ypos = -.1
 scale = 1./df.index.size
 for level in range(df.index.nlevels)[::-1]:
 pos = 0
 for label, rpos in label_len(df.index,level):
 lxpos = (pos + .5 * rpos)*scale
 ax.text(lxpos, ypos, label, ha='center', transform=ax.transAxes)
 add_line(ax, pos*scale, ypos)
 pos += rpos
 add_line(ax, pos*scale , ypos)
 ypos -= .1

df = test_table().groupby(['Room','Shelf','Staple']).sum()
fig = plt.figure()
ax = fig.add_subplot(111)
df.plot(kind='bar',stacked=True,ax=fig.gca())
#Below 3 lines remove default labels
labels = ['' for item in ax.get_xticklabels()]
ax.set_xticklabels(labels)
ax.set_xlabel('')
label_group_bar_table(ax, df)
fig.subplots_adjust(bottom=.1*df.index.nlevels)
plt.show()
</code></pre>
<a href="https://i.stack.imgur.com/KE98i.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/KE98i.png" alt="enter image description here" /></a>

I want to plot data of the following form, using matplotlib bar plot:
<pre><code>data = {'Room A':
 {'Shelf 1':
 {'Milk': 10,
 'Water': 20},
 'Shelf 2':
 {'Sugar': 5,
 'Honey': 6}
 },
 'Room B':
 {'Shelf 1':
 {'Wheat': 4,
 'Corn': 7},
 'Shelf 2':
 {'Chicken': 2,
 'Cow': 1}
 }
 }
</code></pre>
The bar chart is supposed to look
<img src="https://i.stack.imgur.com/w8vgT.png" alt="like this" />
The bar groups should be visible from the labels on the x axis. Is there any way to do this with matplotlib?

How to add group labels for bar charts in matplotlib

我想使用matplotlib条形图绘制以下形式的数据：data = {'Room A':           {'Shelf 1':               {'Milk': 10,                'Water': 20},            'Shelf 2':               {...

问如何在matplotlib中为条形图添加组标签
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