为什么会这样??我哭的好大声
7-6 统计字符串中每个字符出现的次数 (10分)本题目要求读入一个字符串,统计字符串中每个字符出现的次数,输出结果按次数降序排序。
输入格式:
输入一行由任意字符组成的字符串。
输出格式:
输出每个字符出现的次数,输出结果按次数降序排序。
输入样例:
在这里给出一组输入。例如:
This is a good idea.
输出样例:
在这里给出相应的输出。例如:
: 4
i : 3
s : 2
a : 2
o : 2
d : 2
T : 1
h : 1
g : 1
e : 1
. : 1
sentense=str(input())
lst=[]
for i in sentense:
lst.append(i)
l=set(lst)
s=[]
for j in l:
if j in lst:
x=lst.count(j)
s.append((x,j))
s=sorted(s)
s=s.reverse()
for q in s:
print(str(q)+" : "+str(q))
运行结果:
data:image/png;base64,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
d = {}
for c in input():
d . setdefault(c , 0)
d += 1
e = zip(d . values() , d . keys())
f = sorted(e , reverse=True)
for x in f:
print(x , ':' , x) 你这个和我出现的问题是一样的欸{:10_250:} 集合会自动去重的,楼上的代码可用
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