code: def mode(values, dropna=True):
      """
      Returns the mode(s) of an array.
  
      Parameters
      ----------
      values : array-like
          Array over which to check for duplicate values.
      dropna : boolean, default True
          Don't consider counts of NaN/NaT.
  
          .. versionadded:: 0.24.0
  
      Returns
      -------
      mode : Series
      """
      from pandas import Series
  
      values = _ensure_arraylike(values)
      original = values
  
      # categorical is a fast-path
      if is_categorical_dtype(values):
          if isinstance(values, Series):
              return Series(
                  values.values.mode(dropna=dropna), name=values.name
              )
          return values.mode(dropna=dropna)
  
      if dropna and is_datetimelike(values):
          mask = values.isnull()
          values = values[~mask]
  
      values, dtype, ndtype = _ensure_data(values)
  
      f = getattr(htable, "mode_{dtype}".format(dtype=ndtype))
      result = f(values, dropna=dropna)
      try:
          result = np.sort(result)
      except TypeError as e:
          warn("Unable to sort modes: {error}".format(error=e))
  
      result = _reconstruct_data(result, original.dtype, original)
      return Series(result)
  
imports: from __future__ import division
  from textwrap import dedent
  from warnings import catch_warnings, simplefilter, warn
  import numpy
  from pandas._libs import algos, hashtable, lib
  from pandas._libs.tslib import iNaT
  from pandas.util._decorators import Appender, Substitution, deprecate_kwarg
  from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike, maybe_promote
  from pandas.core.dtypes.common import ensure_float64, ensure_int64, ensure_object, ensure_platform_int, ensure_uint64, is_array_like, is_bool_dtype, is_categorical_dtype, is_complex_dtype, is_datetime64_any_dtype, is_datetime64tz_dtype, is_datetimelike, is_extension_array_dtype, is_float_dtype, is_integer_dtype, is_interval_dtype, is_list_like, is_numeric_dtype, is_object_dtype, is_period_dtype, is_scalar, is_signed_integer_dtype, is_sparse, is_timedelta64_dtype, is_unsigned_integer_dtype, needs_i8_conversion
  from pandas.core.dtypes.generic import ABCIndex, ABCIndexClass, ABCSeries
  from pandas.core.dtypes.missing import isna, na_value_for_dtype
  from pandas.core import common
label_desc: Use image node_id 14 for calling a global function with example usage: mode(values, dropna) and returns: Series, values, Series