时间戳

首页 > 解决方案 > 根据字典的值获取键

python - 根据字典的值获取键

问题描述

第一次练习python，就遇到了这个疑惑。使用可变文本，我输入了一个小段落并根据空格将其拆分。所以现在我有了那段的单词，但这是存储在字典中的。接下来，我继续查找段落中每个单词的出现次数。我的最终动机是制作一个出现超过“x”次的单词的新列表。

我的代码是：

text = '''Population refers to the number of individuals in a particular 
place. It could be the number of humans or any other life form living in a 
certain specified area. The number of tigers living in a forest is 
therefore referred to as the population of tigers in the forest. The 
number of people living in a town or city or an entire country is the 
human population in that particular area.'''

words = text.split(" ")
a = dict()
for word in words:
  if word not in a:
    a[word] = 1
  else:
    a[word]+= 1

newlist = list()
val = 7
for key,value in a.items():
  if a[key]>val:
    newlist.append(i)

执行最后一行后我收到的最终输出是：

['years.', 'years.', 'years.', 'years.']

我不知道我哪里错了

标签： pythondictionary

解决方案

为了创建一个以单词为键、出现次数为值的字典，您需要首先获取所有唯一单词。你可以通过使用setPython 的函数来做到这一点。

然后，您遍历该集合并使用 的count方法list，您可以获得每个单词的出现次数。

你可以在下面看到：

text = '''Population refers to the number of individuals in a particular 
place. It could be the number of humans or any other life form living in a 
certain specified area. The number of tigers living in a forest is 
therefore referred to as the population of tigers in the forest. The 
number of people living in a town or city or an entire country is the 
human population in that particular area.'''

words = text.split() # Split text and create a list of all words
wordset = set(words) # Get all unique words
wordDict = dict((word,words.count(word)) for word in wordset) # Create dictionary of words and number of occurences.

for key, value in wordDict.items():
    print(key + ' : ' + str(value))

这会给你：

individuals : 1
forest : 1
the : 5
could : 1
therefore : 1
place. : 1
form : 1
or : 3
country : 1
population : 2
humans : 1
The : 2
city : 1
living : 3
Population : 1
life : 1
in : 6
a : 4
refers : 1
tigers : 2
is : 2
to : 2
be : 1
an : 1
other : 1
as : 1
particular : 2
number : 4
human : 1
It : 1
any : 1
forest. : 1
town : 1
that : 1
certain : 1
of : 5
entire : 1
people : 1
specified : 1
referred : 1
area. : 2

然后，您可以应用自己的过滤器来获取所有出现x多次的单词。

推荐阅读