class_docstr: Base class for generator of stats proto from generic data.
class_docstr_tok: ["Base","class","for","generator","of","stats","proto","from","generic","data","."]
docstr: Converts a Numpy dtype to the FeatureNameStatistics.Type proto enum.
docstr_tok: ["Converts","a","Numpy","dtype","to","the","FeatureNameStatistics.Type","proto","enum","."]
code: def DtypeToType(self, dtype):
      """Converts a Numpy dtype to the FeatureNameStatistics.Type proto enum."""
      if dtype.char in np.typecodes["AllFloat"]:
          return self.fs_proto.FLOAT
      elif (
          dtype.char in np.typecodes["AllInteger"]
          or dtype == bool
          or np.issubdtype(dtype, np.datetime64)
          or np.issubdtype(dtype, np.timedelta64)
      ):
          return self.fs_proto.INT
      else:
          return self.fs_proto.STRING
  
file_path: facets/facets_overview/facets_overview/base_generic_feature_statistics_generator.py
imports: import numpy
  import pandas
  import sys
label_desc: Use image node_id 3 for calling the BaseGenericFeatureStatisticsGenerator obj's underlying member method code with example usage: obj.DtypeToType(dtype) and returns: self, self, self