SPARC Data JSON Converter

This repository contains the SPARC (Spitzer Photometry and Accurate Rotation Curves) database converted into JSON format for easy usage in Jupyter Notebooks and other analysis tools.

Structure

• sparc_data/: Contains the original .dat files from the SPARC database.
• sparc_full.json: Contains the aggregated data for all galaxies in a single file.
• convert_to_json.py: Python script used to perform the conversion.

JSON Format

Each JSON file represents a galaxy and follows this structure:

{
  "meta": {
    "galaxy_name": "GalaxyName",
    "distance": 12.3,
    "distance_unit": "Mpc"
  },
  "columns": ["Rad", "Vobs", "errV", "Vgas", "Vdisk", "Vbul", "SBdisk", "SBbul"],
  "units": ["kpc", "km/s", "km/s", "km/s", "km/s", "km/s", "L/pc^2", "L/pc^2"],
  "data": [
    [0.1, 10.5, 2.1, ...],
    [0.2, 20.3, 1.5, ...]
  ]
}

Columns Description

• Rad: Radius (kpc)
• Vobs: Observed rotation velocity (km/s)
• errV: Uncertainty in observed velocity (km/s)
• Vgas: Velocity contribution from gas (km/s)
• Vdisk: Velocity contribution from the stellar disk (km/s)
• Vbul: Velocity contribution from the bulge (km/s)
• SBdisk: Surface brightness of the disk (L/pc^2)
• SBbul: Surface brightness of the bulge (L/pc^2)

Usage

You can load the entire database easily in Python:

import json
import pandas as pd

# Load all data
with open('sparc_full.json', 'r') as f:
    all_data = json.load(f)

# Access a specific galaxy
galaxy_name = 'CamB'
data = all_data[galaxy_name]

# Access metadata
print(f"Galaxy: {data['meta']['galaxy_name']}, Distance: {data['meta']['distance']} Mpc")

# Convert to Pandas DataFrame
df = pd.DataFrame(data['data'], columns=data['columns'])
print(df.head())

Regeneration

To regenerate the JSON files from the source data:

python3 convert_to_json.py