There is a Pandas Series column: 'loan_amnt' 10 78 54 GOOD 64 23 Write a function that finds all rows with letters in the column and replace them with NaN. Example: find_non_numbers(df, 'loan_amnt') df Result: 10 78 54 NaN 64 23

def find_non_numbers(df, column):
    return df[~df[column].astype(str).str.isnumeric()]