NLP¶
Notebook Cell
# term freq = freq of term 't' in doc 'd' / total terms in 'd'
def tf(doc):
temp_list = doc.split(" ") # split terms
final_dict = {} # store final dictionary with term freq
for i in temp_list:
if i not in final_dict.keys(): # check if term is already present in dict
final_dict[i] = round(temp_list.count(i)/len(temp_list),2) # calculating tf
return final_dict
tf("I have a nice car with a nice tires"){'I': 0.11,
'have': 0.11,
'a': 0.22,
'nice': 0.22,
'car': 0.11,
'with': 0.11,
'tires': 0.11}