Count words in a text file, sort by frequency, and generate a histogram of the top N

word_frequency.py

#!/usr/bin/python

"""Python script to create a histogram of words in a text file.

Usage: python word_frequency.py -f "/path/to/file.txt" -n 200

Specify the path to the text file as above. Manually specify the top N words to report (default 100).

Text file can contain punctuation, new lines, etc., but special characters aren't handled well.

"""

import os
import sys
import string
import argparse
import operator

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

from collections import Counter

__author__ = 'Nick Powell (PhD student, CMIC & CABI, UCL, UK), nicholas.powell.11@ucl.ac.uk'
__version__ = '0.2.20150303'
__created__ = '2014-12-18, Thursday'

    
def main():
    
    parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
    parser.add_argument('-f','--filepath',dest='filepath',metavar='file path',help='Path to text input file to be analysed.', required=True)
    parser.add_argument('-n','--number',dest='number',metavar='number',help='Most frequent n words will be displayed and plotted.', required=False, default=100, type=int)
    args = parser.parse_args()
    
    # Path to text file to analyse
    rawfilepath = args.filepath
    
    # Print a histogram containing the top N words, and print them and their counts.
    top_n = args.number
    
    # Load the file
    filepath = os.path.normpath(os.path.join(rawfilepath))
    file = open(filepath, 'r')
    
    # Parse as a list, removing lines
    content_sublists = [line.split(',') for line in file.readlines()]
    
    # Parse into a single list (from a list of lists)
    content_list = [item for sublist in content_sublists for item in sublist]
    
    # Remove whitespace so we can concatenate appropriately, and unify case
    content_list_strip = [str.strip().lower() for str in content_list]
    
    # Concatenate strings into a single string
    content_concat = ' '.join(content_list_strip)
    
    # Remove punctuation and new lines
    punct = set(string.punctuation)
    unpunct_content = ''.join(x for x in content_concat if x not in punct)
    
    # Split string into list of strings, again
    word_list = unpunct_content.split()
    
    # Perform count
    counts_all = Counter(word_list)
    
    words, count_values = zip(*counts_all.items())
    
    # Sort both lists by frequency in values (Schwartzian transform) - thanks, http://stackoverflow.com/questions/9543211/sorting-a-list-in-python-using-the-result-from-sorting-another-list
    values_sorted, words_sorted = zip(*sorted(zip(count_values, words), key=operator.itemgetter(0), reverse=True))
    
    # Top N
    words_sorted_top = words_sorted[0:top_n]
    values_sorted_top = values_sorted[0:top_n]
    
    print("- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -")
    print("{0} unique words identified in the text file, {1}".format(len(values_sorted), filepath))
    print("The top {0} words are: \n{1}".format(top_n, words_sorted_top))
    print("... their respective frequencies: \n{0}".format(values_sorted_top))
    print("- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -")
    # Pandas DataFrame just for visualisation
    df = pd.DataFrame({'count': values_sorted_top, 'word': words_sorted_top})
    print("{0}".format(df))
    sys.stdout.flush()
    
    # Histogram
    
    # Make xticklabels comprehensible by matplotlib
    xticklabels = unicode(list(words_sorted_top)).split()
    # Remove the single quotes, commas and enclosing square brackets
    xtlabs = [xstr.replace("'","").replace(",","").replace("]","").replace("[","") for xstr in xticklabels]
    
    indices = np.arange(len(words_sorted_top))
    width = 1
    fig = plt.figure()
    fig.suptitle('Word frequency histogram, top {0}'.format(top_n), fontsize=16)
    plt.xlabel('word', fontsize=12)
    plt.ylabel('count', fontsize=12)
    plt.bar(indices, values_sorted_top, width)
    plt.xticks(indices + width * 0.5, xtlabs, rotation='vertical', fontsize=8)
    plt.show()
    
if __name__ == '__main__':
    main()
    
# End