I have been working recently on an independent project using a database for Cybersecurity Attack classification. I imported the database using Pandas (Python) and before starting the processing step, I have noticed that some of the entries contain the following symbols: "-", "0x000b", "0xc0a8", and many others that it is difficult to track them and see how many of these unformatted data are present, specially when the database is so big. Is there a way to take the whole dataframe, spot all the possible unformatted and error data and substitute them by NaN, to treat them later as missing values?
Thanks in advance!