code: def clean_val(val):
      if str(val) in bad_vals_as_strings:
          raise (ValueError("clean_val failed"))
      else:
          try:
              float_val = float(val)
          except ValueError:
              # This will throw a ValueError if it fails
              # remove any commas in the string, and try to turn into a float again
              try:
                  cleaned_string = val.replace(",", "")
                  float_val = float(cleaned_string)
              except TypeError:
                  return None
          return float_val
  
imports: import datetime
  import os
  import dateutil
  import numpy
  import pandas
  from pandas import __version__
  import pathos
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_extraction.text import TfidfVectorizer
  import warnings
label_desc: Use image node_id 1 for calling a global function with example usage: clean_val(val) and returns: float_val, None