ExoData: A python package to handle large exoplanet catalogue data

TL;DR

ExoData is a Python package that facilitates access, analysis, and querying of large exoplanet catalogues, enhancing reproducibility and efficiency in exoplanet research workflows.

Contribution

It introduces a Python interface for the Open Exoplanet Catalogue, enabling object-oriented data handling, advanced querying, and parameter computation for exoplanet research.

Findings

Enables retrieval of exact system parameters used in research articles.

Supports parsing spectral types and filling missing parameters.

Facilitates integration into data pipelines and target selection.

Abstract

Exoplanet science often involves using the system parameters of real exoplanets for tasks such as simulations, fitting routines, and target selection for proposals. Several exoplanet catalogues are already well established but often lack a version history and code friendly interfaces. Software that bridges the barrier between the catalogues and code enables users to improve the specific repeatability of results by facilitating the retrieval of exact system parameters used in an articles results along with unifying the equations and software used. As exoplanet science moves towards large data, gone are the days where researchers can recall the current population from memory. An interface able to query the population now becomes invaluable for target selection and population analysis. ExoData is a Python interface and exploratory analysis tool for the Open Exoplanet Catalogue. It allows the loading of exoplanet systems into Python as objects (Planet, Star, Binary etc) from which common orbital and system equations can be calculated and measured parameters retrieved. This allows researchers to use tested code of the common equations they require (with units) and provides a large science input catalogue of planets for easy plotting and use in research. Advanced querying of targets are possible using the database and Python programming language. ExoData is also able to parse spectral types and fill in missing parameters according to programmable specifications and equations. Examples of use cases are integration of equations into data reduction pipelines, selecting planets for observing proposals and as an input catalogue to large scale simulation and analysis of planets.