class_docstr: Fingerprint of elemental properties from composition.
  
  Based on the data source chosen, returns properties and statistics
  (min, max, range, mean, standard deviation, mode) for a compound
  based on elemental stoichiometry. E.g., the average electronegativity
  of atoms in a crystal structure. The chemical fingerprint is a
  vector of these statistics. For a full list of properties and statistics,
  see ``matminer.featurizers.composition.ElementProperty(data_source).feature_labels()``.
  
  This featurizer requires the optional dependencies pymatgen and
  matminer. It may be useful when only crystal compositions are available
  (and not 3D coordinates).
  
  See references [1]_, [2]_, [3]_, [4]_ for more details.
  
  References
  ----------
  .. [1] MagPie data: Ward, L. et al. npj Comput Mater 2, 16028 (2016).
      https://doi.org/10.1038/npjcompumats.2016.28
  .. [2] Deml data: Deml, A. et al. Physical Review B 93, 085142 (2016).
      10.1103/PhysRevB.93.085142
  .. [3] Matminer: Ward, L. et al. Comput. Mater. Sci. 152, 60-69 (2018).
  .. [4] Pymatgen: Ong, S.P. et al. Comput. Mater. Sci. 68, 314-319 (2013).
  
  Examples
  --------
  >>> import deepchem as dc
  >>> import pymatgen as mg
  >>> comp = mg.core.Composition("Fe2O3")
  >>> featurizer = dc.feat.ElementPropertyFingerprint()
  >>> features = featurizer.featurize([comp])
  >>> type(features[0])
  <class 'numpy.ndarray'>
  >>> features[0].shape
  (65,)
  
  Note
  ----
  This class requires matminer and Pymatgen to be installed.
  `NaN` feature values are automatically converted to 0 by this featurizer.
docstr: Parameters
  ----------
  data_source: str of "matminer", "magpie" or "deml" (default "matminer")
      Source for element property data.
docstr_tok: ["Parameters","--","--","--","--","--","data_source",":","str","of","``","matminer","''",",","``","magpie","''","or","``","deml","''","(","default","``","matminer","''",")","Source","for","element","property","data","."]
code: def __init__(self, data_source: str = "matminer"):
      """
      Parameters
      ----------
      data_source: str of "matminer", "magpie" or "deml" (default "matminer")
          Source for element property data.
      """
      self.data_source = data_source
      self.ep_featurizer: Any = None
  
file_path: deepchem/deepchem/feat/material_featurizers/element_property_fingerprint.py
imports: import numpy
  from deepchem.utils.typing import PymatgenComposition
  from deepchem.feat import MaterialCompositionFeaturizer
  from typing import Any
label_desc: Use image node_id 1 to create a new ElementPropertyFingerprint object from inherited base classes: MaterialCompositionFeaturizer with example: obj = ElementPropertyFingerprint(data_source)