Visualization and data analysis

I developed visualization tools, first in the context of my research in astrophysics (to visualize and analyse data from numerical simulation codes or data analysis codes I used) but also in sociology. I work, most of the time, in Python.

Tools for astrophysics

dumpy

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dumpy is the Python library I wrote to visualize and analyse data from numerical simulations performed with DUMSES-Hybrid. This library can be used to read and visualize data in all available geometries and to reconstruct new variables on the fly (as seen above (second picture) with \(\rho v_x^2\), reconstructed from density \(\rho\) and velocity \(v_x\)).

PyRADMC

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During my doctoral research, I wrote the PyRADMC Python library to read and visualize data from the radiative transfer code RADMC-3D I used to perform synthetic observations of protostellar cores. At this time, RADMC-3D was shipped with IDL routines. PyRADMC can be used to read images and spectra produced with RADMC.

PyTHENA

I also wrote the PyThena library to read output from the hydrodynamics simulation code Athena 3D (Fortran 95 version). I wanted to test the code and was confronted to IDL routines (that used to be quite common in astrophysics and tend to be less so in the past few years).

Sociological data visualization

Job barometer for PhDs

I developed for Adoc Talent Management a job barometer for PhDs in Python, that measures the evolution of the doctorate holders job market in France and abroad.

Survey data visualization

In the framework of my work at Adoc Talent Management, I wrote a tool in Python (and build with Pandas and Dash, an amazing framework to easily build web apps to visualize and analyse data) to visualize data from LimeSurvey.

Representing flux of individuals

Data from longitudinal studies (follow-up of individuals on several years) raise interesting questions in t erms of data visualization. With a bit of R and of D3.js, I made interactive representation of flux of individuals.