← ClaudeAtlas

data-wranglerlisted

Production-grade tabular data manipulation using pandas & openpyxl. This skill should be used when editing, creating, filtering, sorting, merging, pivoting, deduplicating, validating, or transforming CSV, Excel (xlsx/xls), JSON, Parquet, or TSV files. Supports 18 operations via CLI scripts, advanced Excel formatting (multi-sheet, freeze, auto-filter, validation, styling), and file-converter integration for format pipelines.
georgekhananaev/claude-skills-vault · ★ 24 · Data & Documents · score 84
Install: claude install-skill georgekhananaev/claude-skills-vault
# Data Wrangler Manipulate tabular data (CSV, Excel, JSON, Parquet, TSV) w/ pandas-powered scripts. Two scripts cover all operations: `data_wrangler.py` for data ops, `excel_toolkit.py` for Excel-specific features. ## When to Use - User asks to read, edit, filter, sort, or transform CSV/Excel/JSON/Parquet/TSV files - User asks to merge/join datasets, deduplicate, fill missing values, or validate data - User asks to create Excel workbooks w/ formatting, dropdowns, freeze panes, or multi-sheet - User asks to pivot, unpivot, group-by, aggregate, sample, or split datasets - User asks to add computed columns, rename columns, cast types, or apply formulas - User asks to convert between data formats (CSV -> Excel, JSON -> Parquet, etc.) - User asks to inspect/profile data structure, types, nulls, stats ## Prerequisites ```bash # Required pip install pandas openpyxl # Optional (per feature) pip install pyarrow # Parquet support pip install xlrd # Legacy .xls read pip install pandasql # SQL queries on DataFrames pip install fastparquet # Alternative Parquet engine ``` ## Quick Routing | Task | Script | Command | |------|--------|---------| | Inspect/profile data | `data_wrangler.py` | `inspect` | | Filter rows | `data_wrangler.py` | `filter --where "expr"` | | Sort by columns | `data_wrangler.py` | `sort --by Col --desc` | | Group & aggregate | `data_wrangler.py` | `group --by Col --agg "Col:func"` | | Merge/join files | `data_wrangler.py` | `