class_docstr: A custom processing pipeline for the phishing URLs dataset.
class_docstr_tok: ["A","custom","processing","pipeline","for","the","phishing","URLs","dataset","."]
code: def _cols_to_scale(self, df: pd.DataFrame) -> t.List[object]:
      return [
          i
          for i, x in df.dtypes.items()
          if pd.api.types.is_numeric_dtype(x) and i != _target
      ]
  
file_path: deepchecks/deepchecks/tabular/datasets/classification/phishing.py
imports: import typing
  from urllib.request import urlopen
  import joblib
  import pandas
  import sklearn
  from category_encoders import OneHotEncoder
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import Pipeline
  from deepchecks.tabular.dataset import Dataset
label_desc: Use image node_id 1 for calling the UrlDatasetProcessor obj's underlying member method code with example usage: obj._cols_to_scale(df) and returns: unknown