data-analysis is agent-read markdown (skill) from jnpiyush/agentx: Analyze structured data across CSV, JSON, SQL, and DataFrame workflows with exploration, transformation, and visualization. Use when exploring datasets with pandas/polars, running SQL queries on files with DuckDB, transforming data pipelines, or generating data visualizations..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Data Analysis
> Patterns for exploring, transforming, validating, and visualizing structured data.
## Prerequisites
- Python 3.9+ with pandas, polars, or DuckDB installed
## When to Use
- Exploring CSV, JSON, Parquet, or database data
- Building data transformation pipelines
- Validating data quality and schema compliance
- Creating data visualizations and reports
- Writing ETL/ELT scripts
## Decision Tree
```
Working with data?
+- Quick exploration / ad-hoc?
| +- Small file (< 1GB)? -> Pandas / Polars
| +- SQL-like queries? -> DuckDB (in-process)
| - Interactive? -> Jupyter Notebook
+- Production pipeline?
| +- Simple transforms? -> Python script + scheduling
| +- Large scale? -> Spark / Databricks
| - Streaming? -> Kafka + Flink
+- Data validation?
| +- Schema checking? -> Pydantic / Great Expectations
| - Quality rules? -> dbt tests / custom validators
- Visualization?
+- Static charts? -> Matplotlib / Seaborn
+- Interactive? -> Plotly / Altair
- Dashboard? -> Streamlit / Dash
```
## Quick Start: Pandas
```python
import pandas as pd
# Load data
df = pd.read_csv("data.csv")
# Explore
print(df.shape) # (rows, cols)
print(df.dtypes) # Column types
…
Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
GET https://markdownregistry.com/api/v1/artifacts/art_acpzb2zsnr3zpgwx
GET https://markdownregistry.com/api/v1/resolve?ref=jnpiyush/agentx/data-analysis
GET https://markdownregistry.com/api/v1/blob/02930ba099785e986d8a1fdbb4d5aad4899f8ebedfb94b6d99e7626f4133e5fa
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