juliensimon/chandra-x-ray-sources

---
license: cc-by-4.0
pretty_name: "Chandra X-Ray Source Catalog"
language:
- en
description: "Chandra Source Catalog (CSC 2.1) — 28,132 unique X-ray sources detected by the Chandra X-Ray Observatory, with positions, multi-band fluxes, hardness ratios, and variability flags."
task_categories:
- tabular-classification
- tabular-regression
tags:
- space
- x-ray
- chandra
- nasa
- astronomy
- open-data
- tabular-data
size_categories:
- 100K<n<1M
configs:
- config_name: default
data_files:
- split: train
path: data/chandra_x_ray_sources.parquet
default: true
---

# Chandra X-Ray Source Catalog

*Part of the [Astronomy Datasets](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743) collection on Hugging Face.*

The Chandra Source Catalog (CSC 2.1) is the definitive catalog of X-ray sources
detected by NASA's [Chandra X-Ray Observatory](https://chandra.harvard.edu/),
the most powerful X-ray telescope ever built. Currently **28,132** unique sources
across 24 columns.

## Dataset description

The Chandra X-Ray Observatory, launched in 1999, provides the sharpest X-ray images
ever achieved, with sub-arcsecond angular resolution. The Chandra Source Catalog (CSC)
is a comprehensive catalog of all X-ray sources detected in Chandra observations,
including positions, multi-band photometry (soft, medium, hard, broad, wide bands),
hardness ratios for spectral characterization, variability flags, and source extent
measurements.

CSC 2.1 covers roughly 560 square degrees of sky and includes sources from over
15,000 individual Chandra observations. The catalog is essential for multi-wavelength
studies of active galactic nuclei, X-ray binaries, supernova remnants, galaxy clusters,
and stellar coronae.

## Quick stats

- **28,132** unique X-ray sources

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/chandra-x-ray-sources", split="train")
df = ds.to_pandas()

# Brightest sources by broad-band flux
if "flux_aper_b" in df.columns:
top = df.nlargest(10, "flux_aper_b")[["name", "ra", "dec", "flux_aper_b"]]
print(top)

# Sky coverage map
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(12, 6))
ax.scatter(df["ra"], df["dec"], s=0.01, alpha=0.1)
ax.set_xlabel("RA (deg)")
ax.set_ylabel("Dec (deg)")
ax.invert_xaxis()
ax.set_title("Chandra Source Catalog Sky Coverage")
```

## Data source

All data comes from the [Chandra Source Catalog 2.1](https://cxc.cfa.harvard.edu/csc/)
(Evans et al. 2024), accessed via NASA HEASARC TAP service.

## Related datasets

- [erosita-erass1-xray](https://huggingface.co/datasets/juliensimon/erosita-erass1-xray) -- eROSITA eRASS1 X-ray sources
- [fermi-4fgl-dr4](https://huggingface.co/datasets/juliensimon/fermi-4fgl-dr4) -- Fermi gamma-ray sources
- [pulsar-catalog](https://huggingface.co/datasets/juliensimon/pulsar-catalog) -- Pulsar catalog

## Pipeline

Source code: [juliensimon/space-datasets](https://github.com/juliensimon/space-datasets)

## Citation

```bibtex
@dataset{chandra_x_ray_sources,
author = {Simon, Julien},
title = {Chandra X-Ray Source Catalog},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/chandra-x-ray-sources},
note = {Based on Chandra Source Catalog 2.1 (Evans et al. 2024) via NASA HEASARC}
}
```

## License

[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)