code: def value_counts(
      values,
      sort: bool = True,
      ascending: bool = False,
      normalize: bool = False,
      bins=None,
      dropna: bool = True,
  ) -> Series:
      """
      Compute a histogram of the counts of non-null values.
  
      Parameters
      ----------
      values : ndarray (1-d)
      sort : bool, default True
          Sort by values
      ascending : bool, default False
          Sort in ascending order
      normalize: bool, default False
          If True then compute a relative histogram
      bins : integer, optional
          Rather than count values, group them into half-open bins,
          convenience for pd.cut, only works with numeric data
      dropna : bool, default True
          Don't include counts of NaN
  
      Returns
      -------
      Series
      """
      warnings.warn(
          # GH#53493
          "pandas.value_counts is deprecated and will be removed in a "
          "future version. Use pd.Series(obj).value_counts() instead.",
          FutureWarning,
          stacklevel=find_stack_level(),
      )
      return value_counts_internal(
          values,
          sort=sort,
          ascending=ascending,
          normalize=normalize,
          bins=bins,
          dropna=dropna,
      )
  
imports: from __future__ import annotations
  import decimal
  import operator
  from textwrap import dedent
  from typing import TYPE_CHECKING, Literal, cast
  import warnings
  import numpy
  from pandas._libs import algos, hashtable, iNaT, lib
  from pandas._typing import AnyArrayLike, ArrayLike, ArrayLikeT, AxisInt, DtypeObj, TakeIndexer, npt
  from pandas.util._decorators import doc
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike, np_find_common_type
  from pandas.core.dtypes.common import ensure_float64, ensure_object, ensure_platform_int, is_array_like, is_bool_dtype, is_complex_dtype, is_dict_like, is_extension_array_dtype, is_float, is_float_dtype, is_integer, is_integer_dtype, is_list_like, is_object_dtype, is_signed_integer_dtype, needs_i8_conversion
  from pandas.core.dtypes.concat import concat_compat
  from pandas.core.dtypes.dtypes import BaseMaskedDtype, CategoricalDtype, ExtensionDtype, NumpyEADtype
  from pandas.core.dtypes.generic import ABCDatetimeArray, ABCExtensionArray, ABCIndex, ABCMultiIndex, ABCSeries, ABCTimedeltaArray
  from pandas.core.dtypes.missing import isna, na_value_for_dtype
  from pandas.core.array_algos.take import take_nd
  from pandas.core.construction import array, ensure_wrapped_if_datetimelike, extract_array
  from pandas.core.indexers import validate_indices
label_desc: Use image node_id 12 for calling a global function with example usage: value_counts(values, sort, ascending, normalize, bins, dropna) and returns: value_counts_internal