# Algorithms Exercise 1

## Imports

``````

In [258]:

%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.
``````

In [259]:

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.

``````

In [261]:

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') == \
'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.

``````

In [262]:

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

``````
``````

In [263]:

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

``````
``````

In [265]:

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`.
``````

In [277]:

mobydick=open('mobydick_chapter1.txt')

``````
``````

In [280]:

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

``````
``````

In [281]:

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

``````
``````

In [ ]:

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...

``````

In [ ]:

plt.

``````
``````

In [ ]:

assert True # use this for grading the dotplot

``````