docstr: Whether columns with this dtype should be considered numeric.
  
  By default ExtensionDtypes are assumed to be non-numeric.
  They'll be excluded from operations that exclude non-numeric
  columns, like (groupby) reductions, plotting, etc.
docstr_tok: ["Whether","columns","with","this","dtype","should","be","considered","numeric",".","By","default","ExtensionDtypes","are","assumed","to","be","non-numeric",".","They","'ll","be","excluded","from","operations","that","exclude","non-numeric","columns",",","like","(","groupby",")","reductions",",","plotting",",","etc","."]
code: def _is_numeric(self):
      # type: () -> bool
      """
      Whether columns with this dtype should be considered numeric.
  
      By default ExtensionDtypes are assumed to be non-numeric.
      They'll be excluded from operations that exclude non-numeric
      columns, like (groupby) reductions, plotting, etc.
      """
      return False
  
imports: import numpy
  from pandas.errors import AbstractMethodError
  from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries
  from pandas import compat
label_desc: Use image node_id 6 for calling the _DtypeOpsMixin obj's underlying member method code with example usage: obj._is_numeric() and returns: False