code: def test_mean_nan(es):
      array = pd.Series([5, 5, 5, 5, 5])
      mean_func_nans_default = Mean().get_function()
      mean_func_nans_false = Mean(skipna=False).get_function()
      mean_func_nans_true = Mean(skipna=True).get_function()
      assert mean_func_nans_default(array) == 5
      assert mean_func_nans_false(array) == 5
      assert mean_func_nans_true(array) == 5
      array = pd.Series([5, np.nan, np.nan, np.nan, np.nan, 10])
      assert mean_func_nans_default(array) == 7.5
      assert isnan(mean_func_nans_false(array))
      assert mean_func_nans_true(array) == 7.5
      array_nans = pd.Series([np.nan, np.nan, np.nan, np.nan])
      assert isnan(mean_func_nans_default(array_nans))
      assert isnan(mean_func_nans_false(array_nans))
      assert isnan(mean_func_nans_true(array_nans))
  
      # test naming
      default_feat = Feature(
          es["log"].ww["value"],
          parent_dataframe_name="customers",
          primitive=Mean,
      )
      assert default_feat.get_name() == "MEAN(log.value)"
      ignore_nan_feat = Feature(
          es["log"].ww["value"],
          parent_dataframe_name="customers",
          primitive=Mean(skipna=True),
      )
      assert ignore_nan_feat.get_name() == "MEAN(log.value)"
      include_nan_feat = Feature(
          es["log"].ww["value"],
          parent_dataframe_name="customers",
          primitive=Mean(skipna=False),
      )
      assert (
          include_nan_feat.get_name() == "MEAN(log.value, skipna=False)"
      )
  
imports: from datetime import datetime
  from inspect import isclass
  from math import isnan
  import numpy
  import pandas
  import pytest
  from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import Datetime
  from featuretools import AggregationFeature, Feature, IdentityFeature, Timedelta, calculate_feature_matrix, dfs, primitives
  from featuretools.entityset.relationship import RelationshipPath
  from featuretools.feature_base.cache import feature_cache
  from featuretools.primitives import Count, Max, Mean, Median, NMostCommon, NumTrue, NumUnique, Sum, TimeSinceFirst, TimeSinceLast, get_aggregation_primitives
  from featuretools.primitives.base import AggregationPrimitive
  from featuretools.synthesis.deep_feature_synthesis import DeepFeatureSynthesis, match
  from featuretools.tests.testing_utils import backward_path, feature_with_name, to_pandas
  from featuretools.utils.gen_utils import Library
label_desc: Use image node_id 6 for calling a global function with example usage: test_mean_nan(es) without return types