Cleans some eeg data

eeg_clean.py

import pandas as pd
import numpy as np
import sys
import argparse
import time

def eeg_clean(file_input, file_output):
	data1 = pd.read_csv(file_input, sep = ';')
	data1.dropna(inplace = True)

	raw = str(data1['MNI152']).replace("[", "") 
	raw = str(raw).replace("]", "")
	raw = raw.split("\n")[:][:]
	for i in range(len(raw)):
	    raw[i] = raw[i][7:]
	    raw[i] = raw[i].lstrip()
	    raw[i] = raw[i].rstrip()
	    raw[i] = raw[i].strip()
	    raw[i] = raw[i].split(" ")
	    while '' in raw[i]:
	        raw[i].remove('')
	clean_mni = pd.DataFrame(raw)
	clean_mni = clean_mni.drop(columns = [3,4])

	raw = str(data1['RAS-Slicer']).replace("[", "") 
	raw = str(raw).replace("]", "")
	raw = raw.split("\n")[:][:]
	for i in range(len(raw)):
	    raw[i] = raw[i][7:]
	    raw[i] = raw[i].lstrip()
	    raw[i] = raw[i].rstrip()
	    raw[i] = raw[i].strip()
	    raw[i] = raw[i].split(" ")
	    while '' in raw[i]:
	        raw[i].remove('')
	clean_ras = pd.DataFrame(raw)
	clean_ras = clean_ras.drop(columns = [3,4])

	big = pd.DataFrame()

	big['Electrodes'] = data1['Electrodes']
	big['RAS-1'] = clean_ras[0]
	big['RAS-2'] = clean_ras[1]
	big['RAS-3'] = clean_ras[2]

	big['MNI-1'] = clean_mni[0]
	big['MNI-2'] = clean_mni[1]
	big['MNI-3'] = clean_mni[2]
	big['Label'] = data1['ASEG_Region']
	timestamp = str(round(time.time()))
	big['Patient_ID'] = timestamp
	file_output_patient = str(file_output +"_" + timestamp + ".csv" )
	big.to_csv(file_output_patient)


if __name__ == "__main__":

	file_input = "example_coordinates.csv"
	file_output = "cleaned"
	eeg_clean(file_input, file_output)

# To import this file, add
#
# import eeg_clean.py 
# 
# into a new jupyter notebook
#
# To use:
# use the function with 
# eeg_clean(input, ouput)
# make sure to enter both an input file and a output file as a string