Messing around with spaCy and Kerouac

verbsKerouac.py

import matplotlib.pyplot as plt
import spacy
nlp = spacy.load('en_core_web_lg')
import pandas as pd
from collections import Counter

kerouac_raw = open('kerouac.txt').read()
kerouac = nlp(kerouac_raw)

Counter([w.string.strip() for w in kerouac.ents if w.label_ == 'PERSON']).most_common(10)

#Function to give us all the adjectives describing a character
def adjectivesDescribingCharacters(text, character):
    sents = [sent for sent in kerouac.sents if character in sent.string]
    adjectives = []
    for sent in sents:
        for word in sent:
            if character in word.string:
                for child in word.children:
                    if child.pos_ == 'ADJ':
                        adjectives.append(child.string.strip())
    return Counter(adjectives).most_common(10)
  
adjectivesDescribingCharacters(kerouac, 'Sal')
adjectivesDescribingCharacters(kerouac, 'Dean')
adjectivesDescribingCharacters(kerouac, 'Marylou')

#Define a function to give us all the verbs for describing a character
def verbsForCharacters(text, character):
    sents = [sent for sent in kerouac.sents if character in sent.string]
    charWords = []
    for sent in sents: 
        for word in sent: 
            if character in word.string: 
                charWords.append(word)
    charAdjectives = []
    for word in charWords: 
      for ancestor in word.ancestors: 
            if ancestor.pos_.startswith('V'): 
                charAdjectives.append(ancestor.lemma_.strip())
    return Counter(charAdjectives).most_common(20)
  
marylouVerbs = verbsForCharacters(kerouac, 'Marylou')
deanVerbs = verbsForCharacters(kerouac, 'Dean')
salVerbs = verbsForCharacters(kerouac, 'Sal')

#Combine and visualize with Pandas
def verbsToMatrix(verbCounts):
    return pd.Series({t[0]: t[1] for t in verbCounts})

verbsDF = pd.DataFrame({'Marylou': verbsToMatrix(marylouVerbs), 
                        'Dean': verbsToMatrix(deanVerbs), 
                        'Sal': verbsToMatrix(salVerbs)}).fillna(0)
verbsDF.plot(kind='bar', figsize=(16,8))
plt.show()