code: def get_corr_columns(
      df: pd.DataFrame, threshold: float = 0.98
  ) -> list:
      c = df.corr().abs()
      c: pd.DataFrame = c * np.tri(c.shape[0], c.shape[1], -1)
      c = c.transpose()
      return [col for col in c.columns if any(c[col] > threshold)]
  
imports: import warnings
  import pickle
  from time import time
  import numpy
  import pandas
  import shap
  from aix360.algorithms.rbm import BooleanRuleCG, BRCGExplainer, FeatureBinarizer, FeatureBinarizerFromTrees, GLRMExplainer, LogisticRuleRegression
  from aix360.datasets import HELOCDataset, MEPSDataset
  from aix360.datasets.heloc_dataset import nan_preprocessing
  from pandas import DataFrame
  from sklearn.datasets import load_breast_cancer
  from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 7 for calling a global function with example usage: get_corr_columns(df, threshold) and returns: unknown