code: def remove_errors(df: pd.DataFrame) -> utils.Selector:
      df = utils.Selector(df)
      if "error" not in df.columns:  # backward compatibility
          return df  # type: ignore
      # errors with no recommendation
      nandf = df.select(loss=np.isnan)
      for row in nandf.itertuples():
          msg = f'Removing "{row.optimizer_name}"'
          msg += (
              f" with dimension {row.dimension}"
              if hasattr(row, "dimension")
              else ""
          )
          msg += (
              f': got error "{row.error}"'
              if isinstance(row.error, str)
              else "recommended a nan"
          )
          warnings.warn(msg)
      # error with recorded recommendation
      handlederrordf = df.select(
          error=lambda x: isinstance(x, str) and x,
          loss=lambda x: not np.isnan(x),
      )
      for row in handlederrordf.itertuples():
          warnings.warn(
              f'Keeping non-optimal recommendation of "{row.optimizer_name}" '
              f'with dimension {row.dimension if hasattr(row, "dimension") else "UNKNOWN"} which raised "{row.error}".'
          )
      err_inds = set(nandf.index)
      output = df.loc[
          [i for i in df.index if i not in err_inds],
          [c for c in df.columns if c != "error"],
      ]
      # cast nans in loss to infinity
      df.loc[np.isnan(df.loss), "loss"] = float("inf")
      #
      assert (
          not output.loc[:, "loss"].isnull().values.any()
      ), "Some nan values remain while there should not be any!"
      output = utils.Selector(output.reset_index(drop=True))
      return output
  
imports: import os
  import re
  import string
  import hashlib
  import warnings
  import argparse
  import itertools
  from collections import defaultdict
  from pathlib import Path
  import numpy
  import pandas
  from matplotlib import pyplot
  from matplotlib.legend import Legend
  from matplotlib import cm
  from mpl_toolkits.axes_grid1 import make_axes_locatable
  import nevergrad.common.typing
  from .None import utils
  from .exporttable import export_table
label_desc: Use image node_id 6 for calling a global function with example usage: remove_errors(df) and returns: output, df