docstr: Computes Euclidean distance between atoms and a 3D point.
  
  Parameters
  ----------
  xyz : tuple, default: (0.00, 0.00, 0.00)
      X, Y, and Z coordinate of the reference center for the distance
      computation.
  records : iterable, default: ('ATOM', 'HETATM')
      Specify which record sections to consider. For example, to consider
      both protein and ligand atoms, set `records=('ATOM', 'HETATM')`.
      This setting is ignored if `df` is not set to None.
      For downward compatibility, a string argument is still supported
      but deprecated and will be removed in future versions.
  
  Returns
  ---------
  pandas.Series : Pandas Series object containing the Euclidean
      distance between the atoms in the record section and `xyz`.
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code: def distance(
      self, xyz=(0.00, 0.00, 0.00), records=("ATOM", "HETATM")
  ):
      """Computes Euclidean distance between atoms and a 3D point.
  
      Parameters
      ----------
      xyz : tuple, default: (0.00, 0.00, 0.00)
          X, Y, and Z coordinate of the reference center for the distance
          computation.
      records : iterable, default: ('ATOM', 'HETATM')
          Specify which record sections to consider. For example, to consider
          both protein and ligand atoms, set `records=('ATOM', 'HETATM')`.
          This setting is ignored if `df` is not set to None.
          For downward compatibility, a string argument is still supported
          but deprecated and will be removed in future versions.
  
      Returns
      ---------
      pandas.Series : Pandas Series object containing the Euclidean
          distance between the atoms in the record section and `xyz`.
  
      """
  
      if isinstance(records, str):
          warnings.warn(
              "Using a string as `records` argument is "
              "deprecated and will not be supported in future"
              " versions. Please use a tuple or"
              " other iterable instead",
              DeprecationWarning,
          )
          records = (records,)
  
      df = pd.concat(objs=[self.df[i] for i in records])
  
      return np.sqrt(
          np.sum(
              df[["Cartn_x", "Cartn_y", "Cartn_z"]].subtract(
                  xyz, axis=1
              )
              ** 2,
              axis=1,
          )
      )
  
imports: import gzip
  import sys
  import warnings
  from typing import Dict, List, Optional
  from urllib.error import HTTPError, URLError
  from urllib.request import urlopen
  import numpy
  import pandas
  from looseversion import LooseVersion
  from ..pdb.engines import amino3to1dict
  from ..pdb.pandas_pdb import PandasPdb
  from .engines import ANISOU_DF_COLUMNS, MMCIF_PDB_COLUMN_MAP, MMCIF_PDB_NONEFIELDS, PDB_COLUMN_ORDER, mmcif_col_types
  from .mmcif_parser import load_cif_data
label_desc: Use image node_id 18 for calling the PandasMmcif obj's underlying member method code with example usage: obj.distance(xyz, records) and returns: np