<jupyter_start><jupyter_text>Muse Data ExplorationIn this code, we seek to explore the MuSE data<jupyter_code>import pandas as pd
from os import listdir
from os.path import isfile, join
source = '/home/brandon/ExpanDrive/Box/TRI_Data_LREC_2020'<jupyter_output><empty_output><jupyter_text>Video<jupyter_code>s_video_source = source + '/Stressed/Video_Close/processed/'
!ls {s_video_source}
s_video_files = [f for f in listdir(s_video_source) if isfile(join(s_video_source,f))]
pd.read_csv(s_video_source + s_video_files[10])<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10126582278481013, 'fraction_numerical': 0.0108499095840868, 'mean_word_length': 8.892857142857142, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '468657', 'license': 'MIT', 'n_tokens_mistral': 218, 'n_tokens_neox': 210, 'n_words': 40, 'path': 'nbs/data_exploration.ipynb', 'repo_name': 'BrandonThaiTran/muse-analysis', 'size': '553'}