content: import numpy as np
  import pandas as pd
  import scipy.io as sio
  
  from my_settings import *
  
  data = sio.loadmat("/home/mje/Projects/agency_connectivity/Data/data_all.mat")[
      "data_all"]
  
  column_keys = ["subject", "trial", "condition", "shift"]
  result_df = pd.DataFrame(columns=column_keys)
  
  for k, subject in enumerate(subjects):
  
      p8_invol_shift = data[k, 3] - np.mean(data[k, 0])
      p8_vol_shift = data[k, 2] - np.mean(data[k, 0])
      p8_vol_bs_shift = data[k, 1] - np.mean(data[k, 0])
  
      for j in range(89):
          row = pd.DataFrame([{"trial": int(j),
                               "subject": subject,
                               "condition": "vol_bs",
                               "shift": p8_vol_bs_shift[j + 1][0]}])
  
          result_df = result_df.append(row, ignore_index=True)
  
      for j in range(89):
          row = pd.DataFrame([{"trial": int(j),
                               "subject": subject,
                               "condition": "vol",
                               "shift": p8_vol_shift[j + 1][0]}])
  
          result_df = result_df.append(row, ignore_index=True)
  
      for j in range(89):
          row = pd.DataFrame([{"trial": int(j),
                               "subject": subject,
                               "condition": "invol",
                               "shift": p8_invol_shift[j][0]}])
  
          result_df = result_df.append(row, ignore_index=True)
  