How To Count The Number Of Repetation Of Words And Assign A Number And Append Into Dataframe

I am having a dataset of all the abstracts and the author gender. Now i want to get the all the repetitions of words gender wise so that i can plot it as a graph number of repetition of words with respect to gender.

data_path = '/content/digitalhumanities - forum-and-fiction.csv'
def change_table(data_path):
  df = pd.read_csv(data_path)
  final = df.drop(["Title", "Author", "Season", "Year", "Keywords", "Issue No", "Volume"], axis=1)
  fin = final.set_index('Gender')
  return fin
This is the out put i got 
| Gender   | None                                              | Female                                            | Male                                              | None       | None                                  | Male                                              ,Female                                            |None                                              | Male                                             ,Female                                            |
| Abstract | This article describes Virginia Woolf's preocc... | The Amazonian region occupies a singular place... | This article examines Kipling's 1901 novel Kim... | Pamela; or | Virtue Rewarded uses a literary fo... | This article examines Nuruddin Farah's 1979 no... | Ecological catastrophe has challenged the cont... | British political fiction was a satirical genr... | The Lydgates have bought too much furniture an... 

Now how can i get the repetition of each word in the abstract with respect to gender and append to the data frame.

Expecting output example

| This    |    3|     0|   0|
|   occupies  |    5|     3|   0|
| examines    |    6|      0|   0|
|   British  |    0|      0|    7|

. . . enter image description here



Use crosstab with splitting stacked values by DataFrame.stack:

#removed T
df = change_table(data_path)

#reshape with split columns
df = (df.stack()

#explode Type by split with ,
df = df.assign(Type = df['Type'].str.split(',')).explode('Type')

#remove stpowords
from nltk.corpus import stopwords    
stop_words = set(stopwords.words('english'))
df = df[~df['Word'].isin(stop_words)]

#get counts per Gender, Word and Type
df1 = pd.crosstab([df['Gender'], df['Word']], df['Type']).reset_index()

#or get counts per Word and Type
df2 = pd.crosstab([df['Word'], df['Type'])