docstr: Computes Euclidean distance between atoms and a 3D point.
  
  Parameters
  ----------
  df : DataFrame
      DataFrame containing entries in the `PandasPdb.df['ATOM']`
      or `PandasPdb.df['HETATM']` format for the
      the distance computation to the `xyz` reference coordinates.
  xyz : tuple, default: (0.00, 0.00, 0.00)
      X, Y, and Z coordinate of the reference center for the distance
      computation.
  
  Returns
  ---------
  pandas.Series : Pandas Series object containing the Euclidean
      distance between the atoms in the record section and `xyz`.
docstr_tok: ["Computes","Euclidean","distance","between","atoms","and","a","3D","point",".","Parameters","--","--","--","--","--","df",":","DataFrame","DataFrame","containing","entries","in","the","`","PandasPdb.df","[","'ATOM","'","]","`","or","`","PandasPdb.df","[","'HETATM","'","]","`","format","for","the","the","distance","computation","to","the","`","xyz","`","reference","coordinates",".","xyz",":","tuple",",","default",":","(","0.00",",","0.00",",","0.00",")","X",",","Y",",","and","Z","coordinate","of","the","reference","center","for","the","distance","computation",".","Returns","--","--","--","--","-","pandas.Series",":","Pandas","Series","object","containing","the","Euclidean","distance","between","the","atoms","in","the","record","section","and","`","xyz","`","."]
code: def distance_df(df, xyz=(0.00, 0.00, 0.00)):
      """Computes Euclidean distance between atoms and a 3D point.
  
      Parameters
      ----------
      df : DataFrame
          DataFrame containing entries in the `PandasPdb.df['ATOM']`
          or `PandasPdb.df['HETATM']` format for the
          the distance computation to the `xyz` reference coordinates.
      xyz : tuple, default: (0.00, 0.00, 0.00)
          X, Y, and Z coordinate of the reference center for the distance
          computation.
  
      Returns
      ---------
      pandas.Series : Pandas Series object containing the Euclidean
          distance between the atoms in the record section and `xyz`.
  
      """
      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 19 for calling the PandasMmcif obj's underlying member method code with example usage: obj.distance_df(df, xyz) and returns: np