茎叶图

from itertools import groupbynums2=[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 | 5 519 | 520 | 0 0 621 | 0 5 722 | 0 0 0 5 5 5 5 723 | 0 2 2 5 624 | 0 0 0 5 525 | 227 | 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 npimport matplotlib as mplfrom matplotlib import cmimport matplotlib.pyplot as pltfrom 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=0.2ax2.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].theta2center, 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：

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