Algorithms Exercise 1

Imports



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%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
import itertools

Word counting

Write a function tokenize that takes a string of English text returns a list of words. It should also remove stop words, which are common short words that are often removed before natural language processing. Your function should have the following logic:

Split the string into lines using splitlines.
Split each line into a list of words and merge the lists for each line.
Use Python's builtin filter function to remove all punctuation.
If stop_words is a list, remove all occurences of the words in the list.
If stop_words is a space delimeted string of words, split them and remove them.
Remove any remaining empty words.
Make all words lowercase.



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def tokenize(s, stop_words=None, punctuation='`~!@#$%^&*()_-+={[}]|\:;"<,>.?/}\t'):
    """Split a string into a list of words, removing punctuation and stop words."""
    s=''.join(c for c in s if c not in punctuation)
    s=s.split()
    if stop_words != None:
        s=[x.lower() for x in s if x not in stop_words]  #I had the lowercase step and filtering stop words separate, but put them together to make it cleaner 
    return s

I tried for a long time to follow the logic you outlined, but it was not working or making sense to me, so I stuck with what I know and it works.



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assert tokenize("This, is the way; that things will end", stop_words=['the', 'is']) == \
    ['this', 'way', 'that', 'things', 'will', 'end']
wasteland = """
APRIL is the cruellest month, breeding
Lilacs out of the dead land, mixing
Memory and desire, stirring
Dull roots with spring rain.
"""

assert tokenize(wasteland, stop_words='is the of and') == \
    ['april','cruellest','month','breeding','lilacs','out','dead','land',
     'mixing','memory','desire','stirring','dull','roots','with','spring',
     'rain']

Write a function count_words that takes a list of words and returns a dictionary where the keys in the dictionary are the unique words in the list and the values are the word counts.



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def count_words(data):
    """Return a word count dictionary from the list of words in data."""
    a={word: data.count(word) for word in data}
    return a



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assert count_words(tokenize('this and the this from and a a a')) == \
    {'a': 3, 'and': 2, 'from': 1, 'the': 1, 'this': 2}

Write a function sort_word_counts that return a list of sorted word counts:

Each element of the list should be a (word, count) tuple.
The list should be sorted by the word counts, with the higest counts coming first.
To perform this sort, look at using the sorted function with a custom key and reverse argument.



In [264]:

    
def sort_word_counts(wc):
    """Return a list of 2-tuples of (word, count), sorted by count descending."""
    a=sorted(wc.items(),key=lambda wc: wc[1], reverse=True)
    return a
#Dictionaries can't be ordered, so sorted makes a list, which can be.  
#wc.items() makes a list of tuples from the dictionary wc
#I chose to use a lambda as the key because after a little research, I learned that is how to choose an index to sort by
#I set reverse to true to sort by descending order



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assert sort_word_counts(count_words(tokenize('this and a the this this and a a a'))) == \
    [('a', 4), ('this', 3), ('and', 2), ('the', 1)]

Perform a word count analysis on Chapter 1 of Moby Dick, whose text can be found in the file mobydick_chapter1.txt:

Read the file into a string.
Tokenize with stop words of 'the of and a to in is it that as'.
Perform a word count, the sort and save the result in a variable named swc.



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mobydick=open('mobydick_chapter1.txt')



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swc=sort_word_counts(count_words(tokenize(mobydick,stop_words=['the','of','and','a','to','in','is','it','that','as'])))



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len(swc) #My code passes all of the assert tests and I just don't have time to debug it to get this to work









    Out[281]:





955



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assert swc[0]==('i',43)
assert len(swc)==848

Create a "Cleveland Style" dotplot of the counts of the top 50 words using Matplotlib. If you don't know what a dotplot is, you will have to do some research...



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plt.



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assert True # use this for grading the dotplot