text: import pandas as pd
  
  # read the train file to dataframe and drop rows that have no value.
  df = pd.read_csv ('D:/TIF/TIF SEM.7/Frontier Technology/Hotel Recommendations/orange_data/clean_train.csv', sep=',')
  
  # drop the item below, as it is not involved in the process later on.
  # axis 1 refers to the columns.
  df= df.drop('date_time', axis = 1)
  df= df.drop('srch_ci', axis = 1)
  df= df.drop('srch_co', axis = 1)
  
  # .sample = Return a random sample of items from an axis of object.
  # frac = Fraction of axis items to return.
  # random_state = Mersenne Twister pseudo random number generator.
  df = df.sample (frac=0.01, random_state=99)
  # see the shape (rows and columns) of the data (exclude header).
  print(df.shape)
  
  # write the cleaned dataframe result to a new file.
  export_csv = df.to_csv ('D:/TIF/TIF SEM.7/Frontier Technology/Hotel Recommendations/orange_data/clean_train_orange.csv', index = None, header=True)