docstr: Convention: phone number is always presented as int number.
  phone_number = Country code + National Destination Code + Subscriber Number.
  Examples:
  41793834315     for Switzerland
  46767040672     for Sweden
  861065529988    for China
  18143008198     for the USA
  Inplace conversion of phone to int.
  
  Method will remove all non numeric chars from string and convert it to int.
  None will be set for phone numbers that couldn"t be converted to int
docstr_tok: ["Convention",":","phone","number","is","always","presented","as","int","number",".","phone_number","=","Country","code","+","National","Destination","Code","+","Subscriber","Number",".","Examples",":","41793834315","for","Switzerland","46767040672","for","Sweden","861065529988","for","China","18143008198","for","the","USA","Inplace","conversion","of","phone","to","int",".","Method","will","remove","all","non","numeric","chars","from","string","and","convert","it","to","int",".","None","will","be","set","for","phone","numbers","that","couldn","''","t","be","converted","to","int"]
code: def phone_to_int(self):
      """
      Convention: phone number is always presented as int number.
      phone_number = Country code + National Destination Code + Subscriber Number.
      Examples:
      41793834315     for Switzerland
      46767040672     for Sweden
      861065529988    for China
      18143008198     for the USA
      Inplace conversion of phone to int.
  
      Method will remove all non numeric chars from string and convert it to int.
      None will be set for phone numbers that couldn"t be converted to int
      """
      if is_string_dtype(self.df[self.phone_column_name]):
          convert_func = self.phone_str_to_int_safe
      elif is_float_dtype(self.df[self.phone_column_name]):
          convert_func = self.phone_float_to_int_safe
      elif is_int64_dtype(self.df[self.phone_column_name]):
          convert_func = self.phone_int_to_int_safe
      else:
          raise ValidationError(
              f"phone_column_name {self.phone_column_name} doesn't have supported dtype. "
              f"Dataset dtypes: {self.df.dtypes}. "
              f"Contact developer and request to implement conversion of {self.phone_column_name} to int"
          )
      self.df[self.phone_column_name] = (
          self.df[self.phone_column_name]
          .apply(convert_func)
          .astype("Int64")
      )
  
file_path: upgini/src/upgini/normalizer/phone_normalizer.py
imports: from typing import Optional
  import pandas
  from pandas.api.types import is_float_dtype, is_int64_dtype, is_string_dtype
  from upgini.errors import ValidationError
label_desc: Use image node_id 4 for calling the PhoneNormalizer obj's underlying member method code with example usage: obj.phone_to_int() without return types