File data extraction
[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.
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Techniques for parsing TSV/JSON files for financial reporting data (13F).
SKILL.md
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File Data Extraction
When dealing with 13F financial data, the primary data formats encountered are TSV (Tab Separated Values) and JSON.
Parsing TSV
TSV files (like COVERPAGE.tsv and INFOTABLE.tsv) should be treated as structured datasets. Use pandas in Python to quickly aggregate, filter, and compare data.
Example snippet:
import pandas as pd
# Load TSV
df = pd.read_csv('COVERPAGE.tsv', sep='\t')
# Filter for specific fund
fund_data = df[df['name'].str.contains('RENAISSANCE TECHNOLOGIES', case=False)]
Parsing JSON
Metadata files often use JSON. Use the standard json library or pandas.read_json for consistency with TSV processing.