<jupyter_start><jupyter_text>result of experiment:  data for portfolio is missing. Necessary to continue looking and move on to suggestion based analysis in meantime<jupyter_code>import sagemaker
import pandas as pd
tickers = ['SPY', 'SPYV', 'SPYG', 'RSP', 'XMHQ', 'XSMO', 'MDIJX', 'QEFA', 'OGIYX', 'TSEMX', 'PARYX', 'ASHAX', 'AGEYX', 'KBWB', 'XLB', 'SIME', 'FAN', 'TAN', 'PBW']
file_suffix = '_daily_raw_with_3_mo_target.csv'
folder = 'stock_data_raw_with_3_mo_target'
bucket = sagemaker.Session().default_bucket()
d = list()
for ticker in tickers:
    d.append(pd.read_csv(f's3://{bucket}/{folder}/{ticker}{file_suffix}'))
df = d.concat(d, axis=1, key=tickers)
import s3fs
fs = s3fs.S3FileSystem()
files = fs.ls(f's3://{bucket}/{folder}/')
for ticker in tickers:
    file = f's3://{bucket}/{folder}/{ticker}{file_suffix}' in files
    display('{},{}'.format(file, ticker))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1847345132743363, 'fraction_numerical': 0.00995575221238938, 'mean_word_length': 6.357723577235772, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '84986', 'license': 'MIT', 'n_tokens_mistral': 370, 'n_tokens_neox': 351, 'n_words': 79, 'path': 'aws/forecasting/experiements/fbprophet_portfolio.ipynb', 'repo_name': 'Duncan-Haywood/finance_ml_analysis', 'size': '904'}