Duckdb Parquet Lab Workflow
by crossxwill
Use DuckDB to query Parquet files, inspect metadata, join tables, and convert results to pandas for analysis; commonly precedes ydata-eda-profiling for EDA on extracted tables.
Skill Details
Repository Files
2 files in this skill directory
name: duckdb-parquet-lab-workflow description: Use DuckDB to query Parquet files, inspect metadata, join tables, and convert results to pandas for analysis; commonly precedes ydata-eda-profiling for EDA on extracted tables.
DuckDB Parquet Lab Workflow
Purpose
Standardize the pattern of loading Parquet files into DuckDB, inspecting schema, running SQL joins, and converting results to pandas DataFrames.
Usage
- "load Parquet with DuckDB and join tables"
- "describe DuckDB table schema"
- "convert DuckDB query to pandas"
Instructions
- Read Parquet data with
duckdb.queryorduckdb.sqlusing SQL strings. - Inspect schema using
DESCRIBE SELECT * FROM <table>and display with.show(). - Use explicit joins with clear
LEFTorRIGHTsemantics to preserve row counts. - Convert results to pandas with
.to_df()for downstream modeling. - Use
./templates/duckdb_snippets.mdfor the standard SQL patterns.
Related Skills
Xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Clickhouse Io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Clickhouse Io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Analyzing Financial Statements
This skill calculates key financial ratios and metrics from financial statement data for investment analysis
Data Storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
Kpi Dashboard Design
Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.
Dbt Transformation Patterns
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Sql Optimization Patterns
Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.
Anndata
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
Xlsx
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.