code: def counts_to_dicts(df, column):
      
      # index where there are counts and they aren't null
      d = df[column].apply(lambda c: pd.notnull(c) and len(c[0]) > 0)
      return df.loc[d, column].apply(lambda c: {k: v for k, v in zip(*c)})
docs: convert (values, counts) as returned by aggregate.aggregate_counts() to dicts
      makes expand_counts much faster