code: def _set_missing_values(df, columns):
      """Set missing values to NaN. operates in-place."""
      missing_vals = (".", "MISSING_DATA")
      for col in columns:
          # we explicitly use numpy instead of pd.replace because it is faster
          df[col] = np.where(
              df[col].isin(missing_vals), np.nan, df[col]
          )
  
imports: import re
  from datetime import datetime, timedelta, timezone
  import numpy
  from ..._fiff.constants import FIFF
  from ..._fiff.meas_info import create_info
  from ...annotations import Annotations
  from ...utils import _check_pandas_installed, logger, warn
label_desc: Use image node_id 13 for calling a global function with example usage: _set_missing_values(df, columns) without return types