Bigram formation from a given Python list

When we are dealing with text classification, sometimes we need to do certain kind of natural language processing and hence sometimes require to form bigrams of words for processing. In case of absence of appropriate library, its difficult and having to do the same is always quite useful. Let’s discuss certain ways in which this can be achieved.

Method #1 : Using list comprehension + enumerate() + split()
The combination of above three functions can be used to achieve this particular task. The enumerate function performs the possible iteration, split function is used to make pairs and list comprehension is used to combine the logic.

# Python3 code to demonstrate
# Bigram formation
# using list comprehension + enumerate() + split()

# initializing list
test_list = ['geeksforgeeks is best', 'I love it']

# printing the original list
print ("The original list is : " + str(test_list))

# using list comprehension + enumerate() + split()
# for Bigram formation
res = [(x, i.split()[j + 1]) for i in test_list
       for j, x in enumerate(i.split()) if j < len(i.split()) - 1]

# printing result
print ("The formed bigrams are : " + str(res))

Output :

The original list is : [‘geeksforgeeks is best’, ‘I love it’]
The formed bigrams are : [(‘geeksforgeeks’, ‘is’), (‘is’, ‘best’), (‘I’, ‘love’), (‘love’, ‘it’)]

Method #2 : Using zip() + split() + list comprehension
The task that enumerate performed in the above method can also be performed by the zip function by using the iterator and hence in a faster way. Let’s discuss certain ways in which this can be done.

# Python3 code to demonstrate
# Bigram formation
# using zip() + split() + list comprehension

# initializing list
test_list = ['geeksforgeeks is best', 'I love it']

# printing the original list
print ("The original list is : " + str(test_list))

# using zip() + split() + list comprehension
# for Bigram formation
res = [i for j in test_list
       for i in zip(j.split(" ")[:-1], j.split(" ")[1:])]

# printing result
print ("The formed bigrams are : " + str(res))

Output :

The original list is : [‘geeksforgeeks is best’, ‘I love it’]
The formed bigrams are : [(‘geeksforgeeks’, ‘is’), (‘is’, ‘best’), (‘I’, ‘love’), (‘love’, ‘it’)]