hezaohezao/data-analysis
Analyze Excel/CSV files with DuckDB SQL via bash.
npx skills add https://github.com/HezaoHezao/poirot --skill data-analysis
Analyzes user-provided Excel (.xlsx/.xls) or CSV files using DuckDB — an
in-process analytical SQL engine. Supports schema inspection, SQL querying,
statistical summaries, and result export.
> Poirot note: The original deer-flow skill uses a bundled
> scripts/analyze.py helper. Poirot doesn't bundle that script, so this
> version uses bash with python3 + duckdb directly. Install duckdb first:
> pip install duckdb.
# Install duckdb if not present
pip install duckdb openpyxl
python3 -c "
import duckdb
con = duckdb.connect()
# For CSV
result = con.execute(\"DESCRIBE SELECT * FROM read_csv_auto('data.csv')\").fetchall()
for col in result:
print(f'{col[0]:30s} {col[1]}')
# For Excel (each sheet = a table)
result = con.execute(\"SELECT * FROM st_read('data.xlsx', layer='Sheet1') LIMIT 0\").fetchall()
# Row count
count = con.execute(\"SELECT COUNT(*) FROM read_csv_auto('data.csv')\").fetchone()[0]
print(f'Rows: {count}')
"
python3 -c "
import duckdb
con = duckdb.connect()
# Describe statistics
print(con.execute(\"SUMMARIZE SELECT * FROM read_csv_auto('data.csv')\").df().to_string())
"
python3 -c "
import duckdb
con = duckdb.connect()
# Aggregation
result = con.execute('''
SELECT category, COUNT(*) as count, AVG(price) as avg_price
FROM read_csv_auto('data.csv')
GROUP BY category
ORDER BY count DESC
''').fetchall()
for row in result:
print(row)
# Join two files
result = con.execute('''
SELECT a.id, a.name, b.amount
FROM read_csv_auto('orders.csv') a
JOIN read_csv_auto('payments.csv') b ON a.id = b.order_id
''').fetchall()
"
python3 -c "
import duckdb
con = duckdb.connect()
# Export to CSV
con.execute(\"COPY (SELECT * FROM read_csv_auto('data.csv') WHERE amount > 100) TO 'filtered.csv' (HEADER, DELIMITER ',')\")
# Export to JSON
con.execute(\"COPY (SELECT * FROM read_csv_auto('data.csv')) TO 'output.json' (FORMAT JSON)\")
"
SELECT
product,
SUM(CASE WHEN month = 'Jan' THEN amount ELSE 0 END) AS jan,
SUM(CASE WHEN month = 'Feb' THEN amount ELSE 0 END) AS feb,
SUM(CASE WHEN month = 'Mar' THEN amount ELSE 0 END) AS mar
FROM read_csv_auto('sales.csv')
GROUP BY product
SELECT
percentile_cont(0.5) WITHIN GROUP (ORDER BY price) AS median,
percentile_cont(0.95) WITHIN GROUP (ORDER BY price) AS p95
FROM read_csv_auto('data.csv')
python3 -c "
import duckdb
con = duckdb.connect()
# List sheets
sheets = con.execute(\"SELECT table_name FROM st_geometry_tables()\").fetchall()
# Query specific sheet
result = con.execute(\"SELECT * FROM st_read('data.xlsx', layer='Sheet2') LIMIT 10\").fetchall()
"
pip install duckdb openpyxl firstSUMMARIZE on verylarge datasets may be slow. Sample first: SELECT * FROM ... TABLESAMPLE 10%
read_csv_auto options.
explicit strptime parsing.
st_read reads cell values, not formula results. Useopenpyxl directly if you need computed values.
Take hezaohezao/data-analysis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.