code: def _ensure_numeric(x):
      if isinstance(x, np.ndarray):
          if is_integer_dtype(x) or is_bool_dtype(x):
              x = x.astype(np.float64)
          elif is_object_dtype(x):
              try:
                  x = x.astype(np.complex128)
              except (TypeError, ValueError):
                  x = x.astype(np.float64)
              else:
                  if not np.any(x.imag):
                      x = x.real
      elif not (is_float(x) or is_integer(x) or is_complex(x)):
          try:
              x = float(x)
          except Exception:
              try:
                  x = complex(x)
              except Exception:
                  raise TypeError(
                      "Could not convert {value!s} to numeric".format(
                          value=x
                      )
                  )
      return x
  
imports: from distutils.version import LooseVersion
  import functools
  import itertools
  import operator
  import warnings
  import numpy
  from pandas._libs import iNaT, lib, tslibs
  import pandas.compat
  from pandas.core.dtypes.cast import _int64_max, maybe_upcast_putmask
  from pandas.core.dtypes.common import _get_dtype, is_any_int_dtype, is_bool_dtype, is_complex, is_complex_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_float, is_float_dtype, is_integer, is_integer_dtype, is_numeric_dtype, is_object_dtype, is_scalar, is_timedelta64_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import DatetimeTZDtype
  from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna
  import pandas.core.common
  from pandas.core.config import get_option
label_desc: Use image node_id 32 for calling a global function with example usage: _ensure_numeric(x) and returns: x