## 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))```

```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```

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))

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")

# 调整子区布局

# 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)),

#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")