code: def get_treasury_data(start_date, end_date):
      bill_data = load_frame(
          format_bill_url(start_date, end_date, start_date),
          # We skip fewer rows here because we query for fewer bill fields,
          # which makes the header smaller.
          skiprows=18,
      )
      bond_data = load_frame(
          format_bond_url(start_date, end_date, start_date),
          skiprows=22,
      )
      check_known_inconsistencies(bill_data, bond_data)
  
      # dropna('any') removes the rows for which we only had data for one of
      # bills/bonds.
      out = pd.concat([bond_data, bill_data], axis=1).dropna(how="any")
      assert set(out.columns) == set(six.itervalues(COLUMN_NAMES))
  
      # Multiply by 0.01 to convert from percentages to expected output format.
      return out * 0.01
  
file_path: catalyst/catalyst/data/treasuries_can.py
imports: import pandas
  import six
  from toolz import curry
  from toolz.curried.operator import add
label_desc: Use image node_id 5 for calling a global function with example usage: get_treasury_data(start_date, end_date) and returns: unknown