code: def indicator_data(
      indicators: IndicatorCollection,
  ) -> Tuple[List[np.ndarray], List[List[str]]]:
      r"""
      Returns a tuple of a list of series and a list of names of series.
      Each series, `S` is a timeseries of histograms of shape `[T, 10]`,
      where `T` is the number of timesteps.
      `S[:, 0]` is the `global_step`.
      `S[:, 1:10]` represents the distribution at basis points
      `0, 6.68, 15.87, 30.85, 50.00, 69.15, 84.13, 93.32, 100.00`.
  
      Example:
          >>> from labml import analytics
          >>> indicators = analytics.runs('1d3f855874d811eabb9359457a24edc8')
          >>> analytics.indicator_data(indicators)
      """
  
      series, names = _cache.get_indicators_data(indicators)
  
      if not series:
          raise ValueError("No series found")
  
      return series, names
  
imports: from typing import Tuple, Optional, List, overload, Union, TYPE_CHECKING
  import numpy
  from labml.internal.analytics import cache
  from labml.internal.analytics.altair import density
  from labml.internal.analytics.altair import histogram
  from labml.internal.analytics.altair import scatter
  from labml.internal.analytics.altair import binned_heatmap
  from labml.internal.analytics.indicators import IndicatorCollection
  from labml.internal.analytics.models import ModelProbe
  from labml.internal.analytics.models import ValueCollection
  from labml.internal.analytics.models import DeepValueCollection
  from labml.internal.analytics.viz import text_attention
  from labml.internal.analytics.viz import init_inline_viz
label_desc: Use image node_id 19 for calling a global function with example usage: indicator_data(indicators) and returns: series,  names