茎叶图

from itertools import groupby
nums2=[225, 232,232,245,235,245,270,225,240,240,217,195,225,185,200,
       220,200,210,271,240,220,230,215,252,225,220,206,185,227,236]
for k, g in groupby(sorted(nums2), key=lambda x: int(x) // 10):
    print (k, list(g))
   # print(\'k\', k)
   # print(\'g\', list(g))
    lst = map(str, [int(y) % 10 for y in list(g)])
    print (k, \'|\', \' \'.join(lst))

输出：

18 | 5 5
19 | 5
20 | 0 0 6
21 | 0 5 7
22 | 0 0 0 5 5 5 5 7
23 | 0 2 2 5 6
24 | 0 0 0 5 5
25 | 2
27 | 0 1

说明：

1. / 就表示 浮点数除法，返回浮点结果; // 表示整数除法。
2. itertools.groupby 按照分组函数的值对元素进行分组。

>>> from itertools import groupby
>>> x = groupby(range(10), lambda x: x < 5 or x > 8)
>>> for condition, numbers in x:
	print(condition, list(numbers))
输出：
True [0, 1, 2, 3, 4]
False [5, 6, 7, 8]
True [9]

>>> [k for k, g in groupby(\'AAAABBBCCDAABBB\')]
[\'A\', \'B\', \'C\', \'D\', \'A\', \'B\']
>>> [list(g) for k, g in groupby(\'AAAABBBCCD\')]
[[\'A\', \'A\', \'A\', \'A\'], [\'B\', \'B\', \'B\'], [\'C\', \'C\'], [\'D\']]

3. map(function, iterable, ...) 根据提供的函数对指定序列做映射。第一个参数 function 以参数序列中的每一个元素调用 function 函数，返回包含每次 function 函数返回值的新列表。
4. 循环加处理的例子

>>> [int(y) % 10 for y in [22,73,34,92,45]]
[2, 3, 4, 2, 5]

复合饼图

import numpy as np
import matplotlib as mpl
from matplotlib import cm
import matplotlib.pyplot as plt
from matplotlib.patches import ConnectionPatch

# 使图表元素中正常显示中文
mpl.rcParams[\'font.sans-serif\'] = \'SimHei\'
# 使坐标轴刻度标签正常显示负号
mpl.rcParams[\'axes.unicode_minus\'] = False

#制画布
fig = plt.figure(figsize=(9,5.0625), facecolor=\'cornsilk\')
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)

# 调整子区布局
fig.subplots_adjust(wspace=0)

# 大饼图的制作
labels = [\'成都\',\'武汉\',\'昆明\',\'贵阳\',\'西安\',\'其它\']
size = [802,530,477,256,233,307]
# 分裂距离
explode=(0,0,0,0,0,0.1)
ax1.pie(size,                # 数据
        autopct=\'%1.1f%%\',   # 锲形块的数据标签格式
        startangle=30,       # 锲形块开始角度
        labels=labels,
        colors=cm.Blues(range(10, 300, 50)),
        explode=explode)

#小饼图的制作
labels2 = [\'西宁\',\'拉萨\',\'乌鲁木齐\',\'兰州\']
size2 = [102,79, 76, 50]
width=0.2
ax2.pie(size2,
        autopct=\'%1.1f%%\',
        startangle=90,
        labels=labels2,
        colors=cm.Blues(range(10, 300, 50)),
        radius=0.5,
        shadow=False)

#使用ConnectionPatch画出两个饼图的间连线
#先得到饼图边缘的数据
theta1, theta2 = ax1.patches[-1].theta1, ax1.patches[-1].theta2
center, r      = ax1.patches[-1].center, ax1.patches[-1].r
#画出上边缘的连线
x = r*np.cos(np.pi/180*theta2)+center[0]
y = np.sin(np.pi/180*theta2)+center[1]
con1 = ConnectionPatch(xyA=(0, 0.5),
                       xyB=(x,y),
                       coordsA=ax2.transData,
                       coordsB=ax1.transData,
                       axesA=ax2,axesB=ax1)
print(-width/2, 0.5)
print(x,y)

#画出下边缘的连线
x = r*np.cos(np.pi/180*theta1) + center[0]
y = np.sin(np.pi/180*theta1) + center[1]
con2 = ConnectionPatch(xyA=(-0.1, -0.49),
                       xyB=(x,y),
                       coordsA=\'data\',
                       coordsB=\'data\',
                       axesA=ax2,axesB=ax1)

# 添加连接线
for con in [con1, con2]:
    con.set_color(\'gray\')
    ax2.add_artist(con)
    con.set_linewidth(1)

plt.show()

输出：