class_docstr: Reads and cleans data
  
  Parameters
  ----------
  sep : str, defaut = None
       Delimiter to use when reading a csv file.
  
  header : int or None, default = 0.
      If header=0, the first line is considered as a header.
      Otherwise, there is no header.
      Useful for csv and xls files.
  
  to_hdf5 : bool, default = True
      If True, dumps each file to hdf5 format.
  
  to_path : str, default = "save"
      Name of the folder where files and encoders are saved.
  
  verbose : bool, defaut = True
      Verbose mode
class_docstr_tok: ["Reads","and","cleans","data","Parameters","--","--","--","--","--","sep",":","str",",","defaut","=","None","Delimiter","to","use","when","reading","a","csv","file",".","header",":","int","or","None",",","default","=","0",".","If","header=0",",","the","first","line","is","considered","as","a","header",".","Otherwise",",","there","is","no","header",".","Useful","for","csv","and","xls","files",".","to_hdf5",":","bool",",","default","=","True","If","True",",","dumps","each","file","to","hdf5","format",".","to_path",":","str",",","default","=","``","save","''","Name","of","the","folder","where","files","and","encoders","are","saved",".","verbose",":","bool",",","defaut","=","True","Verbose","mode"]
code: def __init__(
      self,
      sep=None,
      header=0,
      to_hdf5=False,
      to_path="save",
      verbose=True,
  ):
      self.sep = sep
      self.header = header
      self.to_hdf5 = to_hdf5
      self.to_path = to_path
      self.verbose = verbose
  
file_path: MLBox/mlbox/preprocessing/reader.py
imports: import sys
  import pickle
  import os
  import time
  import warnings
  import numpy
  import pandas
  from sklearn.preprocessing import LabelEncoder
  from joblib import Parallel, delayed
label_desc: Use image node_id 1 to create a new Reader object  with example: obj = Reader(sep, header, to_hdf5, to_path, verbose)