aharp 0.0.1

AHARP (Analytics & History Auto-Report Printer): a free, offline toolkit for multi-dataset exploration, exportable reports, time-series analysis, rich plotting, and fuzzy-matched NLP queries.

AHARP

Analytics & History Auto-Report Printer

AHARP is a free, offline Python toolkit for exploring one or more tabular datasets using natural-language queries. Under the hood, it leverages Pandas, NumPy, and a lightweight fuzzy‐matching layer to give you:

• Multi-dataset sessions: load multiple CSVs (e.g. load sales.csv as sales)
• Exportable reports: transcript → Markdown or HTML
• Time-series awareness: resample, rolling avg, line plots
• Fuzzy matching: tolerate typos (nulll→null)

📦 Installation

cd aharp
pip install -e ".[full]"

🚀 CLI Usage

python -m aharp sample_data/people.csv

Commands:

• load FILE.csv as ALIAS — load another dataset
• ask ALIAS question or just type a question if only one dataset is loaded
• export markdown report.md
• export html report.html
• help
• exit

📝 Examples

aharp> load sample_data/products.csv as products
aharp> ask main mean of income
aharp> ask products most common product
aharp> type of age
aharp> plot date vs sales
aharp> export markdown session.md
aharp> exit

📊 Time-Series Commands

• ask main resample date by month
• rolling average of temperature over 7 days
• plot date vs sales (line chart)

---

❓ Supported Question Categories

Dataset Shape

• How many rows?
• Number of rows?
• Row count
• How many columns?
• Column count

Schema & Types

• What are the column types?
• Type of each column
• What type is age?
• Describe column types
• Schema summary
• Show data structure
• Dataset info

Missing / Nulls

• Any missing data?
• Are there nulls?
• Missing values?
• Null counts?
• How many nulls per column?
• Which columns have missing?

Zero Values

• Count zeros in column
• Zero values in inventory?
• How many zeros?
• Zero count

Statistical Summaries

• Top / Mode values
• Mean / Average / Compute mean
• Median / Std / Standard deviation
• Range / Min & Max
• Unique / Distinct counts
• Sample values / Examples

Viewing & Exporting Rows

• Show sample rows
• Show top 5 rows / Head
• Show last rows / Tail
• Any duplicates? / Duplicate count
• Drop duplicates / Remove duplicate rows

Time-Series & Plots

• Plot age vs income
• Create scatter of price vs inventory
• Plot distribution / Histogram / Bar chart / Pie chart

Advanced

• Find rows where city = NY
• Search column city for LA
• Favorite column?

🧪 Run Tests

pytest

🚩 Sample Data

• sample_data/people.csv
• sample_data/products.csv