<jupyter_start><jupyter_text>Individual participant characteristics Creates table of individual participant characteristics (good/total electrodes, hemisphere implanted, recording days used, etc.)<jupyter_code>import pandas as pd
from plot_utils import load_data_characteristics, plot_ecog_descript<jupyter_output><empty_output><jupyter_text>Generate table<jupyter_code>rec_days, hemi, surf_tot, surf_good, depth_tot, depth_good, _, part, _, _ = load_data_characteristics()

ages = [44, 20, 33, 19, 31, 37, 26, 33, 20, 34, 34, 22]  # not found in data files
gender = ['M', 'M', 'M', 'F', 'F', 'M', 'M', 'F', 'M', 'M', 'F', 'M']  # not found in data files
surf_elecs = [str(val_good)+' / '+str(val_tot) for val_good, val_tot in zip(surf_good, surf_tot)]
depth_elecs = [str(val_good)+' / '+str(val_tot) for val_good, val_tot in zip(depth_good, depth_tot)]
pd.DataFrame([part, gender, ages, rec_days, hemi, surf_elecs, depth_elecs],
             index=['Participant', 'Gender', 'Age (years)', 'Recording days used', 'Hemisphere implanted',
                    'Surface electrodes: # good / total', 'Depth electrodes: # good / total']).T<jupyter_output><empty_output>
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