code: def _coerce_to_type(x):
      """
      if the passed data is of datetime/timedelta, bool or nullable int type,
      this method converts it to numeric so that cut or qcut method can
      handle it
      """
      dtype = None
  
      if is_datetime64tz_dtype(x.dtype):
          dtype = x.dtype
      elif is_datetime64_dtype(x.dtype):
          x = to_datetime(x).astype("datetime64[ns]", copy=False)
          dtype = np.dtype("datetime64[ns]")
      elif is_timedelta64_dtype(x.dtype):
          x = to_timedelta(x)
          dtype = np.dtype("timedelta64[ns]")
      elif is_bool_dtype(x.dtype):
          # GH 20303
          x = x.astype(np.int64)
      # To support cut and qcut for IntegerArray we convert to float dtype.
      # Will properly support in the future.
      # https://github.com/pandas-dev/pandas/pull/31290
      # https://github.com/pandas-dev/pandas/issues/31389
      elif is_extension_array_dtype(x.dtype) and is_numeric_dtype(
          x.dtype
      ):
          x = x.to_numpy(dtype=np.float64, na_value=np.nan)
  
      if dtype is not None:
          # GH 19768: force NaT to NaN during integer conversion
          x = np.where(x.notna(), x.view(np.int64), np.nan)
  
      return x, dtype
  
imports: from __future__ import annotations
  from typing import Any, Callable, Literal
  import numpy
  from pandas._libs import Timedelta, Timestamp
  from pandas._libs.lib import infer_dtype
  from pandas._typing import IntervalLeftRight
  from pandas.core.dtypes.common import DT64NS_DTYPE, ensure_platform_int, is_bool_dtype, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_extension_array_dtype, is_integer, is_list_like, is_numeric_dtype, is_scalar, is_timedelta64_dtype
  from pandas.core.dtypes.generic import ABCSeries
  from pandas.core.dtypes.missing import isna
  from pandas import Categorical, Index, IntervalIndex, to_datetime, to_timedelta
  from pandas.core import nanops
  import pandas.core.algorithms
label_desc: Use image node_id 4 for calling a global function with example usage: _coerce_to_type(x) and returns: x,  dtype