Tutorial

This is a guide on how to use the you_need_a_dictionary package.

To install the package

Run the following command:

pip install you-need-a-dictionary

When to use functions

Function Use case
analyze_sentiment Analyse sentiment of sentence
fetch_definition Get definition of word
word_replacement See if a word changes the meaning of sentence
translate_sentence Translate sentence
create_wordcloud Visualise synonyms or anyonyms

How to use functions

To use any of the functions, you first need to import the package :

import you_need_a_dictionary as ynd

analyze_sentiment function

The analyze_sentiment function uses nltk VADER module to analyse the sentiment of a sentence. This function only works for sentences in English.

If you need to analyse the sentiment of a sentence in another language, you can use translate_sentence to translate the sentence into English.

It returns a dictionary with 4 sentiment strengths :

  • neg : proportion of text that expresses negative sentiment ,
  • neu : proportion of text that expresses neutral sentiment ,
  • pos : proportion of text that expresses positive sentiment ,
  • compound : aggregated sentiment score that ranges from -1 (most negative) to 1 (most positive)
import nltk
nltk.download("vader_lexicon")
ynd.analyze_sentiment("I absolutely love Kpop")
{'neg': 0.0, 'neu': 0.308, 'pos': 0.692, 'compound': 0.6697}

fetch_definition function

The fetch_definition function uses nltk corpus Wordnet module to find definitions, synonyms and antonyms.

ynd.fetch_definition("star",top_n=2)
'Word: star\nSense 1 (n): (astronomy) a celestial body of hot gases that radiates energy derived from thermonuclear reactions in the interior\nSense 2 (n): someone who is dazzlingly skilled in any field\nSynonyms: ace, adept, champion, genius, hotshot, maven, mavin, sensation, superstar, virtuoso\nAntonyms: None found'

word_replacement function

The word_replacement substitutes a target word in a sentence with a replacement word and calculates the new sentiment score using the analyze_sentiment.

ynd.word_replacement("I Love MDS", "Love", "enjoy", occurrence=1) 
{'New Sentence': 'I enjoy MDS',
 'Previous Sentiment Type': 'Positive',
 'Previous Sentiment Score': 0.808,
 'New Sentiment Type': 'Positive',
 'New Sentiment Score': 0.762}

translate_sentence function

The translate_sentence uses the Google Translate package to translate a sentence into another language. The languages supported and their corresponding language codes that can be found here.

ynd.translate_sentence("Hello world", "fr", source_language="en")
{'translated_text': 'Bonjour le monde',
 'source_language': 'en',
 'target_language': 'fr',
 'error': None}

create_wordcloud function

The create_wordcloud function creates a wordcloud of synonyms and or antonyms. It uses the nltk corpus Wordnet module to find the similarity strength between the given word and it’s synonym/antonym. The larger a word is the more similar it is to the given word.

ynd.create_wordcloud("cold", "It's officially winter, the air outside is cold.")

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