User:Laurier Rochon/prototyping/npl

NPL with NLTK/Python

• Count number of words (word tokens) : len(text)
• Count number of distinct words (word types) : len(set(text))
• The diversity of a text can be found with : len(text) / len(set(text))
• Dispersion plot : shows you usage of certain words in time (useful for quick overviews) (i.e. text.dispersion_plot(['of','the']))
• Collocations : 2 words that are almost always together (i.e. red wine) text.collocations()
• Join/split to create strings/lists from delimiters
• All the words starting with B in text 5. Sorted and unique words only : sorted([w for w in set(text5) if w.startswith('b')])
• Find exact occurrence of a word = text.index('word')
• Find all 4-letter words in a text :

V = set(text8)
fourletter = [w for w in V if len(w)==4]
sorted(fourletter)

• And show their distribution in order

fdist = FreqDist(text5)
vocab = fdist.keys()
for w in vocab:
	if len(w)==4:
		print w

• Find all words containing 'ma' in them, sorted.

res = sorted([w for w in set(text) if 'ma' in w])

• How often a given word occurs in a text, expressed as a percentage

fdist = FreqDist(text)
fdist['word']/len(text)