text mining and text analytics many of these terms are incorrect spellings of otherwise useful onessuch asjaimie is jaime (lannister)milisandre would be melisandreand so on decent game of thrones-specific thesaurus could help us find and replace these misspellings with fuzzy search algorithm this proves data cleaning in text mining can go on indefinitely if you so desirekeeping effort and payoff in balance is crucial here let' now have look at the most frequent words print wordfreqs_cat most_common( print wordfreqs_cat most_common( figure shows the output of asking for the top most common words for each category figure top most frequent words for the "data scienceand "game of thronesposts now this looks encouragingseveral common words do seem specific to their topics words such as "data,"science,and "seasonare likely to become good differentiators another important thing to notice is the abundance of the single character terms such as and ","we'll get rid of these with this extra knowledgelet' revise our data preparation script step revisiteddata preparation adapted this short data exploration has already drawn our attention to few obvious tweaks we can make to improve our text another important one is stemming the terms