如何计算单词出现次数（从特定列表中的单词）并将结果存储在 Python 中的 Pandas Dataframe 中的新列中？

Question

I currently have a list of words about MMA.

I want to create a new column in my Pandas Dataframe called 'MMA Related Word Count'. I want to analyze the column 'Speech' for each row and sum up how often words (from the list under here) occurred within the speech. Does anyone know the best way to do this? I'd love to hear it, thanks in advance!

Please take a look at my dataframe.

CODE EXAMPLE:

import pandas as pd

mma_related_words = ['mma', 'ju jitsu', 'boxing']

data = {
  "Name": ['Dana White', 'Triple H'],
  "Speech": ['mma is a fantastic sport. ju jitsu makes you better as a person.', 'Boxing sucks. Professional dancing is much better.']
}

#load data into a DataFrame object:
df = pd.DataFrame(data)

print(df) 

CURRENT DATAFRAME:

Name	Speech
Dana White	mma is a fantastic sport. ju jitsu makes you better as a person.
Triple H	boxing sucks. Professional wrestling is much better.

--

EXPECTED OUTPUT: Exactly same as above. But at right side new column with 'MMA Related Word Count'. For Dana White: value 2. For Triple HI want value 1.

Answer 1

You can use a regex with str.count :

import re
regex = '|'.join(map(re.escape, mma_related_words))
# 'mma|ju\\ jitsu|boxing'

df['Word Count'] = df['Speech'].str.count(regex, flags=re.I)
# or
# df['Word Count'] = df['Speech'].str.count(r'(?i)'+regex)

output:

         Name                                             Speech  Word Count
0  Dana White  mma is a fantastic sport. ju jitsu makes you b...           2
1    Triple H  Boxing sucks. Professional dancing is much bet...           1

Answer 2

Using simple loop in apply lambda function shall work; Try this;

def fun(string):
    cnt = 0
    for w in mma_related_words:
        if w.lower() in string.lower():
            cnt = cnt + 1
    return cnt

df['MMA Related Word Count'] = df['Speech'].apply(lambda x: fun(string=x))

Same can also be written as;

df['MMA Related Word Count1'] = df['Speech'].apply(lambda x: sum([1 for w in mma_related_words if w.lower() in str(x).lower()]))

Output of df;