Sheetsmith

Overview

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.

Quick start

Place the spreadsheet (CSV, TSV, or XLS/XLSX) inside the workspace or reference it via a full path.

Run

python3 skills/sheetsmith/scripts/sheetsmith.py <command> <path>

with the command described below.

When you modify data, either provide
```
--output new-file
```
to save a copy or pass
```
--inplace
```
to overwrite the source file.
Check
```
references/usage.md
```
for extra sample commands and tips.

Commands

summary

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

--tail

to preview the tail instead of the head.

describe

Runs

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.

preview

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.

filter

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.

transform

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

--inplace

. The preview version (without writing) reuses the same

--rows

--tail

flags as the other commands.

convert

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.

Workflow rules

Always keep a copy of the raw file or write to a new path; the script will only overwrite the original when you explicitly demand
```
--inplace
```
.
Use the same CLI for both exploration (
```
summary
```
,
```
preview
```
,
```
describe
```
) and editing (
```
filter
```
,
```
transform
```
). The
```
--output
```
flag works for filter/transform so you can easily branch results.
Behind the scenes, the script relies on pandas +
```
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).
Use
```
references/usage.md
```
for extended examples (multi-step cleaning, dataset comparison, expression tips) when the basic command descriptions above are not enough.

References

Usage guidelines:
```
references/usage.md
```
(contains ready-to-copy commands, expression patterns, and dataset cleanup recipes).

Resources

GitHub: https://github.com/CrimsonDevil333333/sheetsmith
ClawHub: https://www.clawhub.ai/skills/sheetsmith

Sheetsmith

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Sheetsmith

Overview

Quick start

Commands

summary

describe

preview

filter

transform

convert

Workflow rules

References

Resources

Quick Start

Manual Installation

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