Large Scale Excel Analysis Skill

Mandatory Rules

When total rows >= 10,000, you MUST use the methods in this skill.

Data Scale	Read Strategy	Reason
< 10k rows	`pd.read_excel()` directly	No memory pressure
10k–100k rows	`pd.read_excel()` → convert to Parquet → `pd.read_parquet()` for analysis	Avoid repeated slow reads
100k–1M rows	openpyxl `read_only` + `iter_rows` streaming → Parquet	`pd.read_excel()` will OOM or timeout
> 1M rows	Streaming read + multi-sheet split (Excel max 1,048,576 rows per sheet)	Must chunk

Prohibited:

Do NOT use pd.read_excel() to fully load 100k+ row files
Do NOT search for fonts with fc-list, find ... fonts, or install packages with pip install
Do NOT use df.iterrows() on large DataFrames (use itertuples() or vectorized ops)
Do NOT use df.apply(lambda...) for operations that can be vectorized