text: import sys
  import time
  import numpy as np
  import pandas as pd
  import math
  import warnings
  from transformUtils import transformFUnion
  
  # Make numpy values easier to read.
  np.set_printoptions(precision=3, suppress=True)
  warnings.filterwarnings('ignore') #cleaner, but not recommended
  
  def readNprep():
      # Read and isolate target and training data
      train = pd.read_csv("~/datasets/santander.csv", delimiter=",", header=None)
      santander = train.iloc[1:,2:]
      santander.columns = [*range(0,200)] #rename header from 0 to 199
      print(santander.head())
      print(santander.info())
      return santander
  
  
  X = readNprep()
  
  X_c2 = X.copy(deep=True)
  X_prep = transformFUnion(X_c2, "santander_spec2.json", "santander_sk.dat")
  
  
  
  