code: def combine_filters(filters, dataframe):
      """
      Combine segment filters.
  
      Parameters
      ----------
      filters: Series
          Series indexed by segment names and with values corresponding to segment filters to
          be applied to the data.
      dataframe: DataFrame
          DataFrame to which filters are applied.
  
      Returns
      -------
      DataFrame
          Data filtered to the given combination of segments.
      """
      segments = filters.index.values
      filtered_data = filters[segments[0]].filter(dataframe)
      if len(segments) > 1:
          for i in range(1, len(segments)):
              filtered_data = filters[segments[i]].filter(filtered_data)
  
      return filtered_data
  
imports: import itertools
  from typing import Callable, Dict, Tuple, Union
  import numpy
  import pandas
  import plotly.graph_objects
  from plotly.subplots import make_subplots
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.core.checks import DatasetKind
  from deepchecks.core.errors import DeepchecksProcessError, DeepchecksValueError
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.utils.performance.partition import partition_column
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 2 for calling a global function with example usage: combine_filters(filters, dataframe) and returns: filtered_data