Completed ToolBox 1

frequency.py

@@ -1,16 +1,68 @@
 """ Analyzes the word frequencies in a book downloaded from
-Project Gutenberg """
+Project Gutenberg
+
+John Wen
+ """
 
 import string
 
 
+def remove_punct(textlist):
+    """ A helper function to remove all punctuations from a string while
+    converting the list into a string
+    """
+    cleanedlist = []
+    textlist = textlist.lower().split()
+    for word in textlist:
+        symbols = string.punctuation
+        for i in range (0,len(symbols)):
+            word = word.replace(symbols[i], '')
+        if len(word) > 0:
+            cleanedlist.append(word)
+    return cleanedlist
+
+# print(remove_punct('so people said. They judged it was him, anyway; said this drownded man'))
+
+
 def get_word_list(file_name):
     """ Reads the specified project Gutenberg book.  Header comments,
     punctuation, and whitespace are stripped away.  The function
     returns a list of the words used in the book as a list.
     All words are converted to lower case.
     """
-    pass
+    f = open(file_name, 'r')
+    lines = f.readlines()
+    curr_line = 0
+    while lines[curr_line].find('START OF THIS PROJECT GUTENBERG EBOOK') == -1:
+      curr_line += 1
+      lines = lines[curr_line+1:]
+    """ first part of code removes the headers while the second part cleans the white space
+    and then cleans the string of punctuations using the helper function above
+    """
+    cleanedwhitespace = []
+    cleanedlist = []
+    for words in lines:
+        cleanedwhitespace.append(words.rstrip())
+    for eachstring in cleanedwhitespace:
+        cleanedlist.extend(remove_punct(eachstring))
+    return cleanedlist
+
+
+
+def highestfreqword(d):
+    """ returns the highest value in the dictionary as a tuple pair
+
+    >>> highestfreqword({'the': 5, 'apple': 2, 'is' : 3, 'large' : 15})
+    ('large', 15)
+    >>> highestfreqword({'the': 5, 'apple': 8, 'is' : 3, 'large' : 2})
+    ('apple', 8)
+
+    Functionality: Breaks down the dictionary down into lists of keys and values and
+    picks the highest value and maps that index back to the key.
+    """
+    v=list(d.values())
+    k=list(d.keys())
+    return k[v.index(max(v))], d[k[v.index(max(v))]]
 
 
 def get_top_n_words(word_list, n):
@@ -21,10 +73,21 @@ def get_top_n_words(word_list, n):
     punctuation
     n: the number of words to return
     returns: a list of n most frequently occurring words ordered from most
-    frequently to least frequentlyoccurring
+    frequently to least frequently occuring.
+
     """
-    pass
+    d = dict()
+    for words in word_list:
+        d[words] = d.get(words,0) + 1
+    newdictionary = d
+    listoftups = []
+    while n > 0:
+        listoftups.append(highestfreqword(newdictionary))
+        newdictionary.pop(highestfreqword(newdictionary)[0])
+        n = n - 1
+    return listoftups
 
 if __name__ == "__main__":
-    print("Running WordFrequency Toolbox")
-    print(string.punctuation)
+    print(get_top_n_words(get_word_list('pg32325.txt') ,100))
+    import doctest
+    doctest.testmod(verbose=False)