The Ledger

Data cleaning and visualization dashboard for messy CSV exports

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Description

An automated data processing dashboard that cleans inconsistent CSV entries and generates a visual report. It handles duplicate removal, data normalization, and calculates revenue stats displayed via pivot tables and SVG charts.

Descriptions, tags, and model credits may be AI-generated or inferred from public sources and can be incomplete or wrong. Learn more.

Details

Why this is interesting: Demonstrates sophisticated logical reasoning for data cleaning and reporting in a single code block.
Built with: Qwen3.8-27B Qwen3 14B Qwen3 8B Qwen3 30B-A3B
Tags: #qwen-3-8-27zb-won-every-test-i-m-not-switching-y #experiment

Discovered: YouTube
First posted: YouTube · Aug 17, 2026
Listed: Added 10d ago

Prompt

Clean a messy CSV export. Build a single self-contained HTML dashboard file (no external libraries, everything inline) that cleans this data and reports on it.
Cleaning rules:
- order_id must be unique: if an id appears twice, keep the first row and drop the rest.
- Rows where amount is not a number (like NA or unknown) are excluded from revenue, but report how many you excluded.
- Negative amounts are refunds and must count as negative revenue.
- Region names must be normalized (TX, Texas, texas are all Texas; CA is California; OH is Ohio).
- Dates appear in multiple formats; parse them all: Q1 = Jan-Mar, Q2 = Apr-Jun.
The dashboard must show:
1. A pivot table of total revenue by region (row) and quarter (column), with row totals, column totals, and a grand total. Formatted as dollars with two decimals.
2. A bar chart showing revenue by region using inline SVG or canvas (no chart libraries).
3. A data quality panel: rows received, duplicates dropped, rows excluded, rows counted.
4. A one-line headline stating the top region and its total revenue.
The numbers displayed must be computed correctly from the data. Output only the complete HTML file.

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The Ledger

Data cleaning and visualization dashboard for messy CSV exports

The Ledger media is blocked

Allow external media to connect to the provider and play this content.

Description

Descriptions, tags, and model credits may be AI-generated or inferred from public sources and can be incomplete or wrong. Learn more.

Details

Why this is interesting: Demonstrates sophisticated logical reasoning for data cleaning and reporting in a single code block.
Built with: Qwen3.8-27B Qwen3 14B Qwen3 8B Qwen3 30B-A3B
Tags: #qwen-3-8-27zb-won-every-test-i-m-not-switching-y #experiment

Discovered: YouTube
First posted: YouTube · Aug 17, 2026
Listed: Added 10d ago

Prompt

Clean a messy CSV export. Build a single self-contained HTML dashboard file (no external libraries, everything inline) that cleans this data and reports on it.
Cleaning rules:
- order_id must be unique: if an id appears twice, keep the first row and drop the rest.
- Rows where amount is not a number (like NA or unknown) are excluded from revenue, but report how many you excluded.
- Negative amounts are refunds and must count as negative revenue.
- Region names must be normalized (TX, Texas, texas are all Texas; CA is California; OH is Ohio).
- Dates appear in multiple formats; parse them all: Q1 = Jan-Mar, Q2 = Apr-Jun.
The dashboard must show:
1. A pivot table of total revenue by region (row) and quarter (column), with row totals, column totals, and a grand total. Formatted as dollars with two decimals.
2. A bar chart showing revenue by region using inline SVG or canvas (no chart libraries).
3. A data quality panel: rows received, duplicates dropped, rows excluded, rows counted.
4. A one-line headline stating the top region and its total revenue.
The numbers displayed must be computed correctly from the data. Output only the complete HTML file.

Source

The Ledger

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The Ledger

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