Python – 列出字符串中的单词频率

给定一个单词列表，将每个单词的出现频率映射到字符串中。

Input : test_str = ‘geeksforgeeks is best for geeks and best for CS’, count_list = [‘best’, ‘geeksforgeeks’, ‘computer’] 
Output : [2, 1, 0] 
Explanation : best has 2 occ., geeksforgeeks 1 and computer is not present in string.
Input : test_str = ‘geeksforgeeks is best for geeks and best for CS’, count_list = [‘better’, ‘gfg’, ‘computer’] 
Output : [0, 0, 0] 
Explanation : No word from list present in string. 
 

方法 #1：使用 defaultdict() + 循环 + 列表推导

在此，我们使用 loop + defaultdict() 计算单词频率，然后使用列表推导获取与单词列表对应的所有计数。

Python3

# Python3 code to demonstrate working of
# Divide String into Equal K chunks
# Using list comprehension
from collections import defaultdict
 
# initializing strings
test_str = 'geeksforgeeks is best for geeks and best for CS'
 
# printing original string
print("The original string is : " + str(test_str))
 
# initializing count_list
count_list = ['best', 'geeksforgeeks', 'computer', 'better', 'for', 'and']
 
# computing frequency
res = defaultdict(int)
for sub in test_str.split():
    res[sub] += 1
     
# assigning to list words
res = [res[sub] for sub in count_list]
 
# printing result
print("The list words frequency : " + str(res))

输出

The original string is : geeksforgeeks is best for geeks and best for CS
The list words frequency : [2, 1, 0, 0, 2, 1]

方法 #2：使用 Counter() + 列表推导

在此，Counter() 用于执行计算频率的任务，然后，列表理解用于为列表单词分配频率。

Python3

# Python3 code to demonstrate working of
# Divide String into Equal K chunks
# Using list comprehension
from collections import Counter
 
# initializing strings
test_str = 'geeksforgeeks is best for geeks and best for CS'
 
# printing original string
print("The original string is : " + str(test_str))
 
# initializing count_list
count_list = ['best', 'geeksforgeeks', 'computer', 'better', 'for', 'and']
 
# computing frequency using Counter()
res = Counter(test_str.split())
     
# assigning to list words
res = [res[sub] for sub in count_list]
 
# printing result
print("The list words frequency : " + str(res))

输出

The original string is : geeksforgeeks is best for geeks and best for CS
The list words frequency : [2, 1, 0, 0, 2, 1]