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From qsv-data-wrangling
Convert tabular data between CSV, TSV, Excel, JSONL, Parquet, and other formats with auto-detection, indexing, and verification using qsv tools.
How this skill is triggered — by the user, by Claude, or both
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/qsv-data-wrangling:data-convertThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Convert tabular data files between formats.
Convert tabular data files between formats.
Cowork note: If relative paths don't resolve, call
qsv_get_working_dirandqsv_set_working_dirto sync the working directory.
.csv), TSV (.tsv/.tab), SSV (.ssv).xlsx, .xls, .xlsm, .xlsb).ods).jsonl, .ndjson).csv.sz, etc.)| Format | Command | Extension |
|---|---|---|
| CSV | select (identity) or fmt | .csv |
| TSV | fmt --out-delimiter '\t' | .tsv |
| JSONL | tojsonl | .jsonl |
| JSON | slice --json | .json |
| Parquet | qsv_to_parquet (core tool) | .parquet |
Index: Run qsv_index on the file for fast random access in subsequent steps.
Detect source format: Run qsv_sniff to identify the input format, delimiter, and encoding.
Convert: Use the appropriate command based on the target format:
To CSV (from Excel/JSONL): The MCP server handles this automatically when you pass non-CSV files to any qsv tool. Use qsv_command with excel for explicit control over sheet selection.
To TSV: Use qsv_command with command: "fmt", options: {"out-delimiter": "\t"}.
To JSONL: Use qsv_command with command: "tojsonl".
To Parquet: Use qsv_to_parquet (dedicated core tool).
Verify output: Run qsv_count on the output (if CSV-based) to confirm row count matches input.
--sheet to specify which sheet to convert (default: first sheet)stats --stats-jsonl first for better type inferencefmt commandexcel with --sheet for each sheetnpx claudepluginhub dathere/qsv --plugin qsv-data-wranglingConverts data files between formats like CSV, Parquet, JSON, Excel, GeoJSON using DuckDB. Supports remote inputs and binary outputs Claude cannot generate natively.
Guides qsv-based CSV wrangling with standard workflow order, tool selection matrix for tasks like filtering/joining/aggregating, selection syntax, and pipeline patterns for cleaning/profiling.
Parse, transform, clean, and analyze CSV files: auto-detect formats, filter/sort/merge/pivot, generate stats/outliers, with Python (pandas) and JavaScript examples.