code: def _float_col_is_int(series):
      # test on a small subset for speed
      # yes, a recursive call would be one line shorter.
      if series[:10].isna().any():
          return False
      if (series[:10] != series[:10].astype(int)).any():
          return False
      if series.isna().any():
          return False
      if (series != series.astype(int)).any():
          return False
      return True
  
imports: from importlib.metadata import version
  from joblib import hash
  import warnings
  from warnings import warn
  import numpy
  import pandas
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.compose import make_column_transformer, ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import OneHotEncoder, StandardScaler
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 6 for calling a global function with example usage: _float_col_is_int(series) and returns: True, False, False, False, False