code: def muldiv(df, feature_list):
      for feat in feature_list:
          for feat_two in feature_list:
              if feat == feat_two:
                  continue
              else:
                  df[feat + "/" + feat_two] = df[feat] / (
                      df[feat_two] - df[feat_two].min()
                  )  # zero division guard
                  df[feat + "_X_" + feat_two] = df[feat] * (
                      df[feat_two]
                  )
  
      return df
  
file_path: deltapy/deltapy/interact.py
imports: import numpy
  import pandas
  from statsmodels.tsa.ar_model import AR
  from timeit import default_timer
  from sklearn.tree import DecisionTreeRegressor
  from math import sin, cos, sqrt, atan2, radians, ceil
  import ta
  from gplearn.genetic import SymbolicTransformer
  from scipy import linalg
  import math
label_desc: Use image node_id 3 for calling a global function with example usage: muldiv(df, feature_list) and returns: df