docs: def load(path, filetype=None, as_df=False, retries=None,
           _oid=None, quiet=False, **kwargs):
      '''Load multiple files from various file types automatically.
  
      Supports glob paths, eg::
  
          path = 'data/*.csv'
  
      Filetypes are autodetected by common extension strings.
  
      Currently supports loadings from:
          * csv (pd.read_csv)
          * json (pd.read_json)
  
      :param path: path to config json file
      :param filetype: override filetype autodetection
      :param kwargs: additional filetype loader method kwargs
      '''
      is_true(HAS_PANDAS, "`pip install pandas` required")
      set_oid = set_oid_func(_oid)
  
      # kwargs are for passing ftype load options (csv.delimiter, etc)
      # expect the use of globs; eg, file* might result in fileN (file1,
      # file2, file3), etc
      if not isinstance(path, basestring):
          # assume we're getting a raw dataframe
          objects = path
          if not isinstance(objects, pd.DataFrame):
              raise ValueError("loading raw values must be DataFrames")
      elif re.match('https?://', path):
          logger.debug('Saving %s to tmp file' % path)
          _path = urlretrieve(path, retries)
          logger.debug('%s saved to tmp file: %s' % (path, _path))
          try:
              objects = load_file(_path, filetype, **kwargs)
          finally:
              remove_file(_path)
      else:
          path = re.sub('^file://', '', path)
          path = os.path.expanduser(path)
          # assume relative to cwd if not already absolute path
          path = path if os.path.isabs(path) else pjoin(os.getcwd(), path)
          files = sorted(glob.glob(os.path.expanduser(path)))
          if not files:
              raise IOError("failed to load: %s" % path)
          # buid up a single dataframe by concatting
          # all globbed files together
          objects = []
          [objects.extend(load_file(ds, filetype, **kwargs))
              for ds in files]
  
      if is_empty(objects, except_=False) and not quiet:
          raise RuntimeError("no objects extracted!")
      else:
          logger.debug("Data loaded successfully from %s" % path)
  
      if set_oid:
          # set _oids, if we have a _oid generator func defined
          objects = [set_oid(o) for o in objects]
  
      if as_df:
          return pd.DataFrame(objects)
      else:
          return objects