Frequency analysis of letters, words and arbitrary-length n-tuples of words.
###Basic wordsworth:
####Example 1: Print the top 50 n-words in textfile.txt
$ python wordsworth --filename textfile.txt --top 50
$ python wordsworth -f textfile.txt -t 50
####Example 2: Print the top n-tuples of up to 10 words in textfile.txt
$ python wordsworth --filename textfile.txt --ntuple 10
$ python wordsworth -f textfile.txt -n 10
####Example 3: Ignore the words 'the', 'a' and '--'.
$ python wordsworth --filename textfile.txt --ignore the,a,--
$ python wordsworth -f textfile.txt -i the,a,--
####Example 4: Ignore just '--'.
$ python wordsworth --filename textfile.txt --ignore ,--
$ python wordsworth -f textfile.txt -i ,--
###NLTK-enabled wordsworth: wordsworth-nltk.py provides extended analysis, including a frequency analysis of verbs, nouns, adjectives, pronouns etc. To run this script you will need to install the python Natural Language Toolkit (NLTK) and the Brown dataset which is used for token tagging. Fortunately this is very simple to install.
Step 1. Install NLTK
$ sudo pip install nltk
Step 2. Launch the python interpretter
$ python
Step 3. Download the Brown dataset
>>> import nltk
>>> nltk.download('brown')
>>> nltk.download('punkt')###Example output:
