Is there a Pandas idiom for reading a CSV file with categorical data that has spelling variants?
I have a CSV file with multiple categorical columns, but most of these columns contain messy data due to typing mistakes (e.g., ‘spciulated’, ‘SPICULATED’, etc. for the category ‘spiculated’ of the column ‘margins’). Is there a standard way to deal with such situations?