code: def test_use_previous_pd_dateoffset(es):
      total_events_pd = Feature(
          es["log"].ww["id"],
          parent_dataframe_name="customers",
          use_previous=pd.DateOffset(hours=47, minutes=60),
          primitive=Count,
      )
  
      feature_matrix = calculate_feature_matrix(
          [total_events_pd],
          es,
          cutoff_time=pd.Timestamp("2011-04-11 10:31:30"),
          instance_ids=[0, 1, 2],
      )
      feature_matrix = to_pandas(
          feature_matrix, index="id", sort_index=True
      )
      col_name = list(feature_matrix.head().keys())[0]
      assert (feature_matrix[col_name] == [1, 5, 2]).all()
  
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 25 for calling a global function with example usage: test_use_previous_pd_dateoffset(es) without return types