Parquet Column Mapper
From the author
Reads and transforms Apache Parquet file metadata and column statistics using PyArrow and the Parquet Thrift specification. Maps column types across Delta Lake, Iceberg, and Hudi table formats.
Install
npx skills add agentskillexchange/skills --skill 'Parquet Column Mapper' -a claude-code
Installs to .claude/skills/Parquet-Column-Mapper/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
Want your agent to suggest skills while you type? See how to use skills from your IDE.
Safety checks on SKILL.md
No warnings.
Why 82
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
Similar skills
Closest to this one by what they do and when they are used.
- pyarrow-pythonskillmds/skillmdUse for writing, reviewing, debugging, testing, or optimizing Python code that uses PyArrow arrays, schemas, Tables, RecordBatches, RecordBatchReaders, compute kernels, Dataset scans, Parquet, or Arrow IPC and C data interfaces. Trigger on schema drift, null/type semantics, chunking, batch streaming, predicate projection pushdown, conversion, and memory ownership. Do not use for pandas-only transformations, Polars-only expressions, generic SQL, Arrow Flight service design, C++/Rust Arrow, or Parquet work that does not use PyArrow.Engineering★ 190
- parquet-converterdatadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionConvert construction data to/from Parquet format. Optimize storage, enable fast queries, and integrate with data lakehouses.Other★ 372
- multi-file-excel-parquet-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件并统计规模,支持大文件向 Parquet 格式转换、分类数据统计及可视化报告生成。Documents★ 5.9K
- range-reading-and-large-file-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件,根据数据量动态选择处理策略,支持特定区域数据提取、大文件 Parquet 转换、统计分析及可视化图表生成。Documents★ 5.9K
- pyspark-etlMindrally/skillsBest practices for building performant, testable PySpark ETL pipelines with Spark SQL and Apache Iceberg. Use when writing or reviewing PySpark jobs, designing joins and window functions, working with map/array higher-order functions, or building idempotent cumulative/snapshot table merges.Data★ 286
- apache-hudi-lakehousevaquarkhan/data-engineering-agent-skillsGuides agents through Apache Hudi lakehouse design. Use when managing incremental upserts, record-level mutations, timeline behavior, compaction, and Hudi-based lakehouse tables.Design★ 59
Ratings & reviews
—
no reviews
Tried this skill? Rate it to help others. Sign in
Discussion
Join the discussion. Sign in