class_docstr: `NBA <https://github.com/EnyanDai/FairGNN/tree/main/dataset/NBA>`_ is an NBA on court performance dataset along salary, social engagement etc.
  
  :param data_path: The url where the dataset is found, defaults to :obj:`https://github.com/divelab/DIG_storage/raw/main/fairgraph/datasets/nba/`
  :type data_path: str, optional
  
  :param root: The path to root directory where the dataset is saved, defaults to :obj:`./dataset/nba`
  :type root: str, optional
class_docstr_tok: ["`","NBA","<","https",":","\/\/github.com\/EnyanDai\/FairGNN\/tree\/main\/dataset\/NBA",">","`","_","is","an","NBA","on","court","performance","dataset","along","salary",",","social","engagement","etc",".",":","param","data_path",":","The","url","where","the","dataset","is","found",",","defaults","to",":","obj",":","`","https",":","\/\/github.com\/divelab\/DIG_storage\/raw\/main\/fairgraph\/datasets\/nba\/","`",":","type","data_path",":","str",",","optional",":","param","root",":","The","path","to","root","directory","where","the","dataset","is","saved",",","defaults","to",":","obj",":","`",".\/dataset\/nba","`",":","type","root",":","str",",","optional"]
code: def download(self):
      print("downloading raw files from:", self.data_path)
      if not os.path.exists(self.root):
          os.makedirs(self.root)
  
      for raw_path in self.raw_paths:
          download_url(self.data_path + raw_path, self.root)
  
imports: import torch
  import numpy
  import os
  import pandas
  import scipy.sparse
  import random
  from torch_geometric.data import download_url
label_desc: Use image node_id 3 for calling the NBA obj's underlying member method code with example usage: obj.download() without return types