old_contents: import numpy as np
  # import glob
  import mne
  import pandas as pd
  
  from my_settings import (epochs_folder, tf_folder, subjects_select)
  
  epochs = mne.read_epochs(
      epochs_folder + "0005_target-epo.fif", preload=False)
  times = epochs.times
  
  conditions = ["ctl", "ent"]
  sides = ["right", "left"]
  ROIS = ["rh", "lh"]
  
  from_time = np.abs(times + 0.08).argmin()
  to_time = np.abs(times - 0.02).argmin()
  
  
  data_all = pd.DataFrame()
  
  for subject in subjects_select:
      for condition in conditions:
          for side in sides:
              for roi in ROIS:
                  dat = np.load("%s_pow_%s_side_dSPM_Brodmann.17-%s_start.npy" %
                                (subject, condition, side, roi))
  
                  value = dat[:, :, from_time:to_time].mean(axis=0).mean(axis=0)
                  
                  row = pd.DataFrame([{"subject": subject,
                                       "condition": condition,
                                       "side": side,
                                       "roi": roi,
                                       "power": value}])
                                      
                  df = df.append(row, ignore_index=True)
  
  
new_contents: import numpy as np
  # import glob
  import mne
  import pandas as pd
  
  from my_settings import (epochs_folder, tf_folder)
  
  subjects_select = ["0005", "0006", "0007", "0008", "0009", "0010",
                     "0011", "0015", "0016", "0017", "0020", "0021",
                     "0022", "0024", "0025"]
  
  epochs = mne.read_epochs(
      epochs_folder + "0005_target-epo.fif", preload=False)
  times = epochs.times
  
  conditions = ["ctl", "ent"]
  sides = ["right", "left"]
  ROIS = ["rh", "lh"]
  
  from_time = np.abs(times + 0.08).argmin()
  to_time = np.abs(times - 0.02).argmin()
  
  
  df = pd.DataFrame()
  
  for subject in subjects_select:
      for condition in conditions:
          for side in sides:
              for roi in ROIS:
                  dat = np.load(tf_folder + "%s_pow_%s_%s_dSPM_Brodmann.17-%s_target.npy" %
                                (subject, condition, side, roi))
  
                  value = dat[:, :, from_time:to_time].mean(axis=0).mean(axis=0).mean(axis=0)
                  
                  row = pd.DataFrame([{"subject": subject,
                                       "condition": condition,
                                       "side": side,
                                       "roi": roi,
                                       "power": value}])
                                      
                  df = df.append(row, ignore_index=True)
  
  
subject: fix syntax