Applying function to Column AttributeError: 'int' object has no attribute-CodePudding

I have a pandas data frame that consists of special/vanity numbers.

numbers = [539249751,530246444,539246655,539209759,538849098]
  
# Create the pandas DataFrame with column name is provided explicitly
vanity_class= pd.DataFrame(numbers, columns=['MNM_MOBILE_NUMBER'])

I would like to add a column to classify each number based on its pattern using regex.

I have written a function that iterates through the column MNM_MOBILE_NUMBER. Identifies the pattern of each number using regex. Then, creates a new column MNC_New_Class with the relevant classification.

def vanity_def(vanity_class):
    if vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'^5(\d)\1{7}') | \
            vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'^5(?!(\d)\1)\d(\d)\2{6}$') | \
            vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'.{2}(?!(\d)\1)\d(\d)\2{5}$') | \
            vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'^\d*(\d)(\d)(?:\1\2){3}\d*$') | \
            vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'^5((\d)\2{3})((\d)\4{3})$') | \
            vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'.{3}(1234567$)'):
        vanity_class['MNC_New_Class'] = 'Diamond'
    elif vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'.{3}(?!(\d)\1)\d(\d)\2{4}$') | \
             vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'^(?!(\d)\1)\d((\d)\3{6})(?!\3)\d$') | \
             vanity_class.MNM_MOBILE_NUMBER.astype(str).str.match(r'\d(\d)\1(\d)\2(\d)\3(\d)\4'):     
        vanity_class['MNC_New_Class'] = 'Gold'
    else:
        vanity_class['MNC_New_Class'] = 'Non Classified'

Then, I wrote this line of code to apply the function to the column.

vanity_class['MNC_New_Class']  = vanity_class['MNM_MOBILE_NUMBER'].apply(vanity_def)

However, I keep getting this error

AttributeError: 'int' object has no attribute 'MNM_MOBILE_NUMBER'

Any advice on how to avoid this error?

Thank you

CodePudding user response：

When you pass a function to Pandas' apply(), it receives the value of the selected column, not the data frame itself. So you should rewrite your code accordingly:

def vanity_def(mnm_mobile_number): # parameter is an int
    # return the new value, do the assignment outside of this function