列表元素的距离
本帖最后由 loengsan 于 2020-4-29 23:44 编辑data:image/png;base64,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各位大佬，比如我有【A,B,C,D,E】这样一个列表，现想得出两两元素间的距离，有什么简单易懂的方法吗？小白求指教。万分感谢
e到b的距离是？ str1 = input('输入：')
list1 =[]
for i in str1:
list1.append(i)
for i in range(len(list1)):
for j in range(i + 1, len(list1)):
print('%c和%c的距离是%d' % (list1, list1, j - i))
#执行结果
输入：ABCDE
A和B的距离是1
A和C的距离是2
A和D的距离是3
A和E的距离是4
B和C的距离是1
B和D的距离是2
B和E的距离是3
C和D的距离是1
C和E的距离是2
D和E的距离是1 wp231957 发表于 2020-4-30 06:58
e到b的距离是？
e到b也是3 list1 = ['A', 'B', 'C', 'D', 'E']
print('D 到 B 的距离是：', abs(list1.index('D') - list1.index('B')))
print('A 到 E 的距离是：', abs(list1.index('A') - list1.index('E')))
print('E 到 F 的距离是：', abs(list1.index('E') - list1.index('F'))) zltzlt 发表于 2020-4-30 13:18
简单粗暴{:10_256:} 麻麦皮 发表于 2020-4-30 07:36
谢谢您{:9_226:}
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