sheetsmith by crimsondevil333333/sheetsmith
npx skills add https://github.com/crimsondevil333333/sheetsmith --skill sheetsmithSheetsmith 是一个轻量级的 pandas 封装工具,专注于处理 CSV/Excel 文件:在一个地方预览、描述、筛选、转换和转换它们。CLI 位于 skills/sheetsmith/scripts/sheetsmith.py,它会自动加载任何 CSV/TSV/Excel 文件,报告结构元数据,运行 pandas 表达式,并安全地将结果写回。
python3 skills/sheetsmith/scripts/sheetsmith.py <命令> <路径>,命令如下所述。--output new-file 来保存副本,要么传递 --inplace 来覆盖源文件。references/usage.md 以获取额外的示例命令和提示。打印行/列计数、数据类型细分、包含缺失数据的列以及头部/尾部预览。使用 --rows 控制摘要后显示多少行,使用 --tail 预览尾部而不是头部。
Sheetsmith is a lightweight pandas wrapper that keeps the focus on working with CSV/Excel files: previewing, describing, filtering, transforming, and converting them in one place. The CLI lives at skills/sheetsmith/scripts/sheetsmith.py, and it automatically loads any CSV/TSV/Excel file, reports structural metadata, runs pandas expressions, and writes the results back safely.
python3 skills/sheetsmith/scripts/sheetsmith.py <command> <path> with the command described below.--output new-file to save a copy or pass --inplace to overwrite the source file.references/usage.md for extra sample commands and tips.Prints row/column counts, dtype breakdowns, columns with missing data, and head/tail previews. Use --rows to control how many rows are shown after the summary and to preview the tail instead of the head.
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运行 pandas.DataFrame.describe(include='all')(可使用 --include 自定义),以便您立即查看数值统计、基数和频率信息。提供 --percentiles 以添加额外的百分位线。
显示前几行(--rows)或后几行(--tail)的快速表格化预览,以便您在采取行动前检查列顺序或格式。
通过 --query 输入一个 pandas 查询字符串(例如,state == 'CA' and population > 1e6)。该命令可以打印筛选后的行,或者当您同时传递 --output 时,将筛选后的表格写入新的 CSV/TSV/XLSX 文件。添加 --sample 以检查随机子集而不是整个结果。
组合新列,重命名或删除现有列,并立即检查结果表。提供一个或多个 --expr 表达式,例如 total = quantity * price。使用 --rename old:new 和 --drop column 来重塑表格,并通过 --output 或 --inplace 持久化更改。预览版本(不写入)重用与其他命令相同的 --rows/--tail 标志。
在支持的格式(CSV/TSV/Excel)之间进行转换。始终使用所需的扩展名指定 --output,助手将检测适当的写入器(Excel 使用 openpyxl,CSV 默认保留逗号分隔符,TSV 使用制表符)。这是在运行其他命令之前规范化数据的最简单方法。
--inplace 时才会覆盖原始文件。summary、preview、describe)和编辑(filter、transform)。--output 标志适用于 filter/transform,因此您可以轻松地分支结果。tabulate 进行 Markdown 预览,并支持 Excel/CSV/TSV,因此请确保这些依赖项存在(pandas、openpyxl、xlrd、tabulate 已通过 apt 在此系统上安装)。references/usage.md 获取扩展示例(多步骤清理、数据集比较、表达式提示)。references/usage.md(包含可直接复制的命令、表达式模式和数据集清理方法)。每周安装数
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--tailRuns pandas.DataFrame.describe(include='all') (customizable with --include) so you instantly see numeric statistics, cardinality, and frequency information. Supply --percentiles to add additional percentile lines.
Shows a quick tabulated peek at the first (--rows) or last (--tail) rows so you can sanity-check column order or formatting before taking actions.
Enter a pandas query string via --query (e.g., state == 'CA' and population > 1e6). The command can either print the filtered rows or, when you also pass --output, write the filtered table to a new CSV/TSV/XLSX file. Add --sample to inspect a random subset instead of the entire result.
Compose new columns, rename or drop existing ones, and immediately inspect the resulting table. Provide one or more --expr expressions such as total = quantity * price. Use --rename old:new and --drop column to reshape the table, and persist changes via --output or --inplace. The preview version (without writing) reuses the same --rows/--tail flags as the other commands.
Convert between supported formats (CSV/TSV/Excel). Always specify --output with the desired extension, and the helper will detect the proper writer (Excel uses openpyxl, CSV preserves the comma separator by default, TSV uses tabs). This is the simplest way to normalize data before running other commands.
--inplace.summary, preview, describe) and editing (filter, transform). The --output flag works for filter/transform so you can easily branch results.tabulate for Markdown previews and supports Excel/CSV/TSV, so ensure those dependencies are present (pandas, openpyxl, xlrd, tabulate are installed via apt on this system).references/usage.md for extended examples (multi-step cleaning, dataset comparison, expression tips) when the basic command descriptions above are not enough.references/usage.md (contains ready-to-copy commands, expression patterns, and dataset cleanup recipes).Weekly Installs
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