Data Cleaning With Python, Data Analysis, Dataframes Python, Marketing Analytics.
number"].str.replace("+","00") phones # Replace "-" with nothing phones["Phone number"] = phones["Phone number"].str.replace("-","") phones # Replace phone numbers with lower than 10 digits to NaN digits = phones['Phone number'].str.len() phones.loc[digits <10,"Phone number"] = np.nan phones Ex11.