Algorithms Exercise 1

Imports



In [1]:

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

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.



In [2]:

    
file = open('mobydick_chapter1.txt')
mobydick = file.read()
mobydick.splitlines()
mobydick.split()
print (len(mobydick.split()))



In [3]:

    
def tokenize(s, stop_words=None, punctuation='`~!@#$%^&*()_-+={[}]|\:;"<,>.?/}\t'):
    lines = s.splitlines()
    i = 0
    empty = []
    while i < len.lines:
        empty.extend(lines[i].split())
        i += 1
    a = []
    b = 0
    while b < len(empty):
        a.append(''.join([c for c in empty[b] if c not in punctuation]))
        b += 1
    for g in a:
        g.lower()    
    c = 0
    d = []
    while c < len(h):
        d.append(''.join([e for e in h[c] if h[c] not in stop_words]))
        c+=1
    answer = list(filter(None,d))
    return answer
    
    """Split a string into a list of words, removing punctuation and stop words."""



In [4]:

    
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']









    



---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-4-cb7875c10e3e> in <module>()
----> 1 assert tokenize("This, is the way; that things will end", stop_words=['the', 'is']) ==     ['this', 'way', 'that', 'things', 'will', 'end']
      2 wasteland = """
      3 APRIL is the cruellest month, breeding
      4 Lilacs out of the dead land, mixing
      5 Memory and desire, stirring

<ipython-input-3-034065b48e22> in tokenize(s, stop_words, punctuation)
      3     i = 0
      4     empty = []
----> 5     while i < len.lines:
      6         empty.extend(lines[i].split())
      7         i += 1

AttributeError: 'builtin_function_or_method' object has no attribute 'lines'

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.



In [5]:

    
def count_words(data):
    """Return a word count dictionary from the list of words in data."""



In [6]:

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









    



---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-6-71b7cc9f406e> in <module>()
----> 1 assert count_words(tokenize('this and the this from and a a a')) ==     {'a': 3, 'and': 2, 'from': 1, 'the': 1, 'this': 2}

<ipython-input-3-034065b48e22> in tokenize(s, stop_words, punctuation)
      3     i = 0
      4     empty = []
----> 5     while i < len.lines:
      6         empty.extend(lines[i].split())
      7         i += 1

AttributeError: 'builtin_function_or_method' object has no attribute 'lines'

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 [7]:

    
"""Return a list of 2-tuples of (word, count), sorted by count descending."""









    Out[7]:





'Return a list of 2-tuples of (word, count), sorted by count descending.'



In [8]:

    
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)]









    



---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-8-2b19d16a049a> in <module>()
----> 1 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)]

NameError: name 'sort_word_counts' is not defined

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.



In [ ]:



In [9]:

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









    



---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-9-79f30673d9f4> in <module>()
----> 1 assert swc[0]==('i',43)
      2 assert len(swc)==848

NameError: name 'swc' is not defined

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...



In [ ]:



In [14]:

    
assert True # use this for grading the dotplot