Co-occurrence matrix from nested list of words

Question

I have a list of names like:

names = [\'A\', \'B\', \'C\', \'D\']

and a list of documents, that in each documents some of these names are m

Answer 1

'''for a window of 2, data_corpus is the series consisting of text data, words is the list consisting of words for which co-occurence matrix is build'''

"co_oc is the co-occurence matrix"

co_oc=pd.DataFrame(index=words,columns=words)

for j in tqdm(data_corpus):

    k=j.split()

    for l in range(len(k)):

        if l>=5 and l<(len(k)-6):
            if k[l] in words:
                for m in range(l-5,l+6):
                    if m==l:
                        continue
                    elif k[m] in words:
                        co_oc[k[l]][k[m]]+=1

        elif l>=(len(k)-6):
            if k[l] in words:
                for m in range(l-5,len(k)):
                    if m==l:
                        continue
                    elif k[m] in words:
                        co_oc[k[l]][k[m]]+=1

        else:
            if k[l] in words:
                for m in range(0,l+5):
                    if m==l:
                        continue
                    elif k[m] in words:
                        co_oc[k[l]][k[m]]+=1
print(co_oc.head())