NLP

Problem: [OKCUPID] Term Frequency

Say you are given a text document in the form of a string with the following sentences:

Input

document = "I have a nice car with a nice tires"

Output

{ "I":0.11, "have":0.11, "a":0.22, "nice":0.22, "car": 0.11, "with":0.11, "tires":0.11 } Write a program in python to determine the TF (term frequency) values for each term of this document.

# 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}