<jupyter_start><jupyter_text>BackgroundThe directory structure currently looks like this:* `Driving Performance`    * `01`        * `Log_20200130101256_Unknown Road__0_0_0.csv`The primary directory (`Driving Performance`) contains folders named based on participant numbers (e.g. folder `00` contains the files related to participant number 00.)Inside each folder, there are CSV files named `Log__Unknown Road__0_0_0` (e.g. `Log_20200130101256_Unknown Road__0_0_0`).There are 21 folders, ranging from 00-21, with 9 log files per folder.  RequirementsRename each log file from `Log__Unknown Road__0_0_0` to `_` (e.g. `01_06`).The trial sequence is this constant set of numbers: [06, 07, 14, 09, 13, 01, 18, 02, 11].The elements of the trial sequence should match each alphabetically-arranged log file. (Arranging the files alphabetically also arranges them based on datetime). ExceptionsFor folders `00` and `11`, the trial sequence element is already indicated in the file name so for example, simply format the log file inside folder `00` from `Log_20200129211416_Unknown Road__0_0_0_6` to `00_06`. Output locationTo preserve the original files, save the parsed files inside a new folder named `parsed_files`.  ScriptImport the os, csv, shutil, and re modules.<jupyter_code>import os # for accessing and creating directories
import csv # for accessing and generating csv files
import shutil # for copying files from one directory to another
import re # for filtering string using regex<jupyter_output><empty_output><jupyter_text>Define the trial sequence.<jupyter_code>trial_sequence = [6, 7, 14, 9, 13, 1, 18, 2, 11]<jupyter_output><empty_output><jupyter_text>Define the paths of the source and destination directories and create them if they don't exist yet.<jupyter_code>src_path = "Driving Performance/"
if not os.path.exists(src_path):
    os.mkdir(src_path)

dst_path = "parsed_files/"
if not os.path.exists(dst_path):
    os.mkdir(dst_path)<jupyter_output><empty_output><jupyter_text>Create dummy folders and CSV files.**NOTE: No need to run this part on actual parsing.**<jupyter_code># creates 9 pre-formatted dummy CSV files
def createDummyFiles(path, folder):
    
    # create a loop from 0-8
    for i in range(9):
        
        # define the pre-formatted dummy filename
        if folder in ["00", "11"]:
            filename = "Log_2020022312345" + str(i) + "_Unknown Road__0_0_0_" + str(trial_sequence[i])
        else:
            filename = "Log_2020022312345" + str(i) + "_Unknown Road__0_0_0"
        
        # create the empty CSV file
        with open(path + filename + ".csv", "w") as dummy:
            pass

# create a loop from 0-20 for the folder names
for i in range(21):
    
    # define the name and path of the directory to be created
    folder = "{:02d}".format(i)
    path = src_path + folder + "/"
    
    # create the folder
    os.makedirs(path)
    
    # create dummy files
    createDummyFiles(path, folder)<jupyter_output><empty_output><jupyter_text>Copy and rename files.<jupyter_code># loop through the folder in Driver Performance
for folder in os.listdir(src_path):
        
        # loop through the files inside each folder
        for index, file in enumerate(os.listdir(src_path + folder + "/")):
            
            # for folders 00 and 11
            if folder in ["00", "11"]:
                
                # filter file to get trial_sequence_element
                trial_sequence_element = re.search(r'Unknown Road__0_0_0_(.*?)\.csv', file).group(1)
                
                # define the formatted filename (format: <folder>_<trial_sequence_element>.csv)
                filename = folder + "_" + "{:02d}".format(int(trial_sequence_element)) + ".csv"

            # for the rest of the folders
            else:
                
                # define the formatted filename (format: <folder>_<trial_sequence_element>.csv)
                filename = folder + "_" + "{:02d}".format(trial_sequence[index]) + ".csv"

            # define the paths of the source and destination files
            src_file = src_path + folder + "/" + file
            dst_file = dst_path + filename

            # create renamed copy of source file
            if not os.path.exists(dst_file):
                shutil.copy(src_file, dst_file)<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup