Add Spreadsheet Data Quality Audit fictional sample - #9
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This pull request adds a new entry, "Spreadsheet Data Quality Audit - Fictional Sample", to the tabular data quality section of the English, Japanese, and Chinese README files. The feedback suggests removing these entries because they represent a static fictional sample and promotional material rather than an actual functional tool or library, which does not align with the curation standards of the list.
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| - [Pandas Profiling](https://github.com/pandas-profiling/pandas-profiling) - A tool for generating profile reports from pandas DataFrames. (2016) | ||
| - [DataProfiler](https://github.com/capitalone/DataProfiler) - A Python library for data profiling and data quality validation. (2021) | ||
| - [Spreadsheet Data Quality Audit - Fictional Sample](https://github.com/ja9740913/spreadsheet-data-quality-audit-sample) - A fixed fictional XLSX input with redacted Excel, Markdown, and JSON audit outputs; sample only, not an audit engine. (2026) |
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This entry is a static fictional sample rather than an actual tool, library, or general-purpose resource. Awesome lists are typically curated to include functional tools, libraries, frameworks, or comprehensive educational resources. Since this repository only contains static sample outputs and serves as a funnel/promotion for a paid toolkit, it does not fit the criteria for the 'Tools & Projects' section. It is recommended to remove this entry to maintain the quality and focus of the list.
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| - [Pandas Profiling](https://github.com/pandas-profiling/pandas-profiling) - pandas DataFrameからプロファイルレポートを生成するツール。(2016) | ||
| - [DataProfiler](https://github.com/capitalone/DataProfiler) - データプロファイリングとデータ品質検証のためのPythonライブラリ。(2021) | ||
| - [Spreadsheet Data Quality Audit - Fictional Sample](https://github.com/ja9740913/spreadsheet-data-quality-audit-sample) - 固定された架空の XLSX 入力と、機密値を除いた Excel、Markdown、JSON 形式の監査出力。サンプルのみで、監査エンジンは含みません。(2026) |
There was a problem hiding this comment.
This entry is a static fictional sample rather than an actual tool, library, or general-purpose resource. Awesome lists are typically curated to include functional tools, libraries, frameworks, or comprehensive educational resources. Since this repository only contains static sample outputs and serves as a funnel/promotion for a paid toolkit, it does not fit the criteria for the 'Tools & Projects' section. It is recommended to remove this entry to maintain the quality and focus of the list.
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| - [Pandas Profiling](https://github.com/pandas-profiling/pandas-profiling) - 从pandas DataFrame生成概要报告的工具。(2016) | ||
| - [DataProfiler](https://github.com/capitalone/DataProfiler) - 用于数据分析和数据质量验证的Python库。(2021) | ||
| - [Spreadsheet Data Quality Audit - Fictional Sample](https://github.com/ja9740913/spreadsheet-data-quality-audit-sample) - 一个固定的虚构 XLSX 输入，附有脱敏的 Excel、Markdown 和 JSON 审计输出；仅为样本，不含审计引擎。(2026) |
There was a problem hiding this comment.
This entry is a static fictional sample rather than an actual tool, library, or general-purpose resource. Awesome lists are typically curated to include functional tools, libraries, frameworks, or comprehensive educational resources. Since this repository only contains static sample outputs and serves as a funnel/promotion for a paid toolkit, it does not fit the criteria for the 'Tools & Projects' section. It is recommended to remove this entry to maintain the quality and focus of the list.
1 participant
I own the linked repository.
This contribution adds one free, fully fictional tabular-data quality evidence sample under Tabular Data > Tools & Projects. It provides one fixed XLSX input and redacted Excel, Markdown, and JSON audit outputs so reviewers can inspect what a completed audit package looks like. It is a sample only, not an open-source audit engine.
The linked README includes a clearly labeled optional paid Toolkit upgrade. This pull request links only the free GitHub sample and adds no Gumroad or affiliate URL.
Why include it: the current entries are executable profiling tools; this sample adds a compact, inspectable output example for spreadsheet practitioners. I updated README.md, README_zh.md, and README_ja.md for consistency.