Multiple text columns

In this exercise, you will continue working with the airline Twitter data. A dataset tweets has been imported for you.

In some situations, you might have more than one text column in a dataset and you might want to create a numeric representation for each of the text columns. Here, besides the text column, which contains the body of the tweet, there is a second text column, called negativereason. It contains the reason the customer left a negative review.

Your task is to build BOW representations for both columns and specify the required stop words.

Import the vectorizer package and the default list of English stop words.
Update the default list of English stop words and create the my_stop_words set.
Specify the stop words argument in the first vectorizer to the updated set, and in the second vectorizer - the default set of English stop words.

Exercise

Multiple text columns

Instructions