code: def _set_df_dtypes(df_dict):
      from mne.utils import _set_pandas_dtype
  
      for key, df in df_dict.items():
          if key in ["samples"]:
              # convert missing position values to NaN
              _set_missing_values(df, df.columns[1:])
              _set_pandas_dtype(
                  df, df.columns, float, verbose="warning"
              )
          elif key in ["blinks", "fixations", "saccades"]:
              _set_missing_values(df, df.columns[1:])
              _set_pandas_dtype(
                  df, df.columns[1:], float, verbose="warning"
              )
          elif key == "messages":
              _set_pandas_dtype(
                  df, ["time"], float, verbose="warning"
              )  # timestamp
      return df_dict
  
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 12 for calling a global function with example usage: _set_df_dtypes(df_dict) and returns: df_dict