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What is the word count tool?
In order to count the words in your document you can use the TextChunk class Word count tool. Lettria’s word count tool enables you to quickly and easily extract the word, part of speech and occurrences within your document. You can also filter out those words by POS tags to enable further analysis of the words within your document.
Importing the library & your personal API key
After you've installed the Lettria package on Python you'll need to import the library.
Next you are going to need to include your personal API key which can be found
via the Lettria platform in the dashboard.
api_key = 'your personal API key' nlp = lettria.NLP(api_key)
Adding your document
Now you will need to open your saved document. Be sure to add the name of
‘your file’ since it may differ from the name of my example file.
with open("example.txt", "r") as f: example_data = f.readlines()
Next, add the document to the NLP.
Extracting the word count
In order to extract the words of the document use the following command:
word_count = nlp.word_count word_count(filter_pos = None, lemma=False)
In the results you will have a list of words, part of speech and number of occurrences.
Extracting additional details
If you would like to filter out parts of speech such as ‘noun’ you can change the filter criteria.
word_count = nlp.word_count word_count(filter_pos = ’N’, lemma=False)
Now you can see within the results all the words and number of occurrences falling under ‘noun’ has been filtered out.
Saving your results
In order to save your results you can use the following command.
And a json file with your results that can be used for further analysis will be saved.
import lettria api_key = 'your personal API key' nlp = lettria.NLP(api_key) with open("example.txt", "r") as f: example_data = f.readlines() nlp.add_document(example_data) word_count = nlp.word_count word_count(filter_pos = None, lemma=False) word_count = nlp.word_count word_count(filter_pos = ’N’, lemma=False) nlp.save_results(‘example_results')