code: def compute_hll_array(obj, b):
      # b is the number of bits
  
      if not 8 <= b <= 16:
          raise ValueError("b should be between 8 and 16")
      num_bits_discarded = 32 - b
      m = 1 << b
  
      # Get an array of the hashes
      hashes = hash_pandas_object(obj, index=False)
      if isinstance(hashes, pd.Series):
          hashes = hashes._values
      hashes = hashes.astype(np.uint32)
  
      # Of the first b bits, which is the first nonzero?
      j = hashes >> num_bits_discarded
      first_bit = compute_first_bit(hashes)
  
      # Pandas can do the max aggregation
      df = pd.DataFrame({"j": j, "first_bit": first_bit})
      series = df.groupby("j").max()["first_bit"]
  
      # Return a dense array so we can concat them and get a result
      # that is easy to deal with
      return series.reindex(np.arange(m), fill_value=0).values.astype(
          np.uint8
      )
  
imports: from __future__ import annotations
  import numpy
  import pandas
  from pandas.util import hash_pandas_object
label_desc: Use image node_id 2 for calling a global function with example usage: compute_hll_array(obj, b) and returns: series