[Python] Text analysis: finding the most common word in a column

I have created a dataframe with just a column with the subject line.

df = activities.filter(['Subject'],axis=1)
df.shape


This returned this dataframe:

Subject
0 Call Out: Quadria Capital - May Lo, VP
1 Call Out: Revelstoke - Anthony Hayes (Sr Assoc...
2 Columbia Partners: WW Worked (Not Sure Will Ev...
3 Meeting, Sophie, CFO, CDC Investment
4 Prospecting


I then tried to analyse the text with this code:

import nltk
top_N = 50
txt = df.Subject.str.lower().str.replace(r'\|', ' ')
words = nltk.tokenize.word_tokenize(txt)
word_dist = nltk.FreqDist(words)

stopwords = nltk.corpus.stopwords.words('english')
words_except_stop_dist = nltk.FreqDist(w for w in words if w not in stopwords)

rslt = pd.DataFrame(word_dist.most_common(top_N), columns=['Word', 'Frequency'])
print(rslt)


The error message I get is: 'Series' object has no attribute 'Subject'

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