# Data Analysis

High-performance data analysis using Polars - load, transform, aggregate, visualize and...

- Repository: https://github.com/melandlabs/openloomi (1038 stars)
- Category: Data and ML
- License: Apache-2.0
- Last updated: 2026-09-24
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add melandlabs/openloomi --skill data_analysis -g -a claude-code -y`
Codex: `npx skills add melandlabs/openloomi --skill data_analysis -g -a codex -y`
Cursor: `npx skills add melandlabs/openloomi --skill data_analysis -g -a cursor -y`
Gemini CLI: `npx skills add melandlabs/openloomi --skill data_analysis -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add melandlabs/openloomi`

## Description

High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Data Analysis Skill

Comprehensive data analysis toolkit using **Polars** - a blazingly fast DataFrame library. This skill provides instructions, reference documentation, and ready-to-use scripts for common data analysis tasks.

### Iteration Checkpoints

| Step | What to Present | User Input Type |
|------|-----------------|-----------------|
| Data Loading | Shape, columns, sample rows | "Is this the right data?" |
| Data Exploration | Summary stats, data quality issues | "Any columns to focus on?" |
| Transformation | Before/after comparison | "Does this transformation look correct?" |
| Analysis | Key findings, charts | "Should I dig deeper into anything?" |
| Export | Output preview | "Ready to save, or any changes?" |

## Quick Start

```python
import polars as pl
from polars import col

# Load data
df = pl.read_csv("data.csv")

# Explore
print(df.shape, df.schema)
df.describe()

# Transform and analyze
result = (
    df.filter(col("value") > 0)
    .group_by("category")
    .agg(col("value").sum().alias("total"))
    .sort("total", descending=True)
)

# Export
result.write_csv("output.csv")
```

## When to Use This Skill

- Loading datasets (CSV, JSON, Parquet, Excel, databases)
- Data cleaning, filtering, and transformation
- Aggregations, grouping, and pivot tables
- Statistical analysis and summary statistics
- Time series analysis and resampling
- Joining and merging multiple datasets
- Creating visualizations and charts
- Exporting results to various formats

## Skill Contents

### Reference Documentation

Detailed API reference and patterns for specific operations:

The rest: https://github.com/melandlabs/openloomi/blob/HEAD/benchmark/GDPval-AA v2/harness/Stirrup/skills/data_analysis/SKILL.md