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Python for Data Science: Identifying Email Threats

Remove StopwordsRemove Stopwords

Removing stopwords is a common preprocessing step in natural language processing (NLP) tasks. Stopwords are words that are commonly used in a language, such as 'a', 'an', 'the', 'and', 'or', etc. They are considered to be of little value in text analysis because they do not carry much meaning on their own.

There are several reasons why removing stopwords is important:

  • Stopwords take up a lot of space in the text and increase the size of the dataset. Removing them can help reduce the size of the dataset and make it more manageable for further processing;
  • Stopwords can also slow down text analysis algorithms. Since they are so common, they can make up a large proportion of the text, making it more computationally expensive to process;
  • Stopwords can also add noise to text analysis, making it harder to extract meaningful insights. They do not add much value to the analysis and can make it harder to identify patterns or topics in the text;
  • Stopwords can also bias the results of text analysis, especially if the analysis is based on word frequency. By removing stopwords, the analysis can focus on the meaningful words and give more accurate results.

Task

  1. Import nltk and some of its libraries;
  2. Select english stopwords;
  3. Use the apply() function to remove them.

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Section 1. Chapter 6