Coming back to our running example of the text from Romeo and Juliet Act 2, Scene 2, we can augment our program to use this technique to print the ten most common words in the text as follows:
import stringfhand = open('romeo-full.txt')counts = dict()for line in fhand: line = line.translate(None, string.punctuation) line = line.lower() words = line.split() for word in words: if word not in counts: counts[word] = 1 else: counts[word] += 1# Sort the dictionary by valuelst = list()for key, val in counts.items(): lst.append( (val, key) ) lst.sort(reverse=True) for key, val in lst[:10] : print key, val
The first part of the program which reads the file and computes the dictionary that maps each word to the count of words in the document is unchanged. But instead of simply printing out counts and ending the program, we construct a list of (val, key) tuples and then sort the list in reverse order.
Since the value is first, it will be used for the comparisons and if there is more than one tuple with the same value, it will look at the second element (the key) so tuples where the value is the same will be further sorted by the alphabetical order of the key.
At the end we write a nice for loop which does a multiple assignment iteration and prints out the ten most common words by iterating through a slice of the list (lst[:10]).
So now the output finally looks like what we want for our word frequency analysis.
61 i42 and40 romeo34 to34 the32 thou32 juliet30 that29 my24 thee
The fact that this complex data parsing and analysis can be done with an easy-tounderstand 19 line Python program is one reason why Python is a good choice as a language for exploring information.