<jupyter_start><jupyter_text>Review DS new file format<jupyter_code>pwd
import pandas as pd
!cat ../../zzData_RAW/header.txt | grep Name > ../../zzData_RAW/header2.txt
f = pd.read_table ('../../zzData_RAW/header2.txt', header=None )
cols = f.iloc[:,0].str.split('=').str.get(1)
df_new = pd.read_table ('../../zzData_RAW/BRSalesNew.txt',header=None, index_col=[0,1,2],names=cols, dtype=object)
df_new.GLANI = df_new.GLANI.astype('str')
df_new.head().T
df_new.GLANI.unique<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.204, 'fraction_numerical': 0.014, 'mean_word_length': 5.109756097560975, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '398509', 'license': 'MIT', 'n_tokens_mistral': 214, 'n_tokens_neox': 203, 'n_words': 29, 'path': 'develop/2017-01-23 tc Daily Sales .ipynb', 'repo_name': 'trevor-crowley/jnb_trump_train', 'size': '500'}