code: def test_repair_zeroes_daily(self):
      tkr = "BBIL.L"
      dat = yf.Ticker(tkr, session=self.session)
      tz_exchange = dat.fast_info["timezone"]
  
      df_bad = _pd.DataFrame(
          data={
              "Open": [0, 102.04, 102.04],
              "High": [0, 102.1, 102.11],
              "Low": [0, 102.04, 102.04],
              "Close": [103.03, 102.05, 102.08],
              "Adj Close": [102.03, 102.05, 102.08],
              "Volume": [560, 137, 117],
          },
          index=_pd.to_datetime(
              [
                  _dt.datetime(2022, 11, 1),
                  _dt.datetime(2022, 10, 31),
                  _dt.datetime(2022, 10, 30),
              ]
          ),
      )
      df_bad = df_bad.sort_index()
      df_bad.index.name = "Date"
      df_bad.index = df_bad.index.tz_localize(tz_exchange)
  
      repaired_df = dat._fix_zeroes(
          df_bad, "1d", tz_exchange, prepost=False
      )
  
      correct_df = df_bad.copy()
      correct_df.loc["2022-11-01", "Open"] = 102.080002
      correct_df.loc["2022-11-01", "Low"] = 102.032501
      correct_df.loc["2022-11-01", "High"] = 102.080002
      for c in ["Open", "Low", "High", "Close"]:
          self.assertTrue(
              _np.isclose(
                  repaired_df[c], correct_df[c], rtol=1e-8
              ).all()
          )
  
      self.assertTrue("Repaired?" in repaired_df.columns)
      self.assertFalse(repaired_df["Repaired?"].isna().any())
  
imports: from .context import yfinance
  from .context import session_gbl
  import unittest
  import os
  import datetime
  import pytz
  import numpy
  import pandas
label_desc: Use image node_id 8 for calling the TestPriceRepair obj's underlying member method code with example usage: obj.test_repair_zeroes_daily() without return types