![]() Nevertheless, consider some possible objectives we may have when working with this text document. We are going to look at general text cleaning steps in this tutorial. I’m sure there is a lot more going on to the trained eye. “II” and “III”), and we have removed the first “I”. There does not appear to be numbers that require handling (e.g.There’s a lot of use of the em dash (“-“) to continue sentences (maybe replace with commas?).There’s hyphenated descriptions like “armour-like”.There’s punctuation like commas, apostrophes, quotes, question marks, and more.There are no obvious typos or spelling mistakes.The lines are artificially wrapped with new lines at about 70 characters (meh).The translation of the original German uses UK English (e.g.It’s plain text so there is no markup to parse (yay!).Poor Gregor… Text Cleaning Is Task SpecificĪfter actually getting a hold of your text data, the first step in cleaning up text data is to have a strong idea about what you’re trying to achieve, and in that context review your text to see what exactly might help. ![]() One morning, when Gregor Samsa woke from troubled dreams, he found himself transformed in his bed into a horrible vermin.Īnd, as if in confirmation of their new dreams and good intentions, as soon as they reached their destination Grete was the first to get up and stretch out her young body. The start of the clean file should look like: Open the file and delete the header and footer information and save the file as “ metamorphosis_clean.txt“. The file contains header and footer information that we are not interested in, specifically copyright and license information.
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