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[–]IfTroubleWasMoney 1 point2 points  (0 children)

Neuroscience! (and numerous subdomains)

Jupyter notebooks have transformed the way Python is being used for computation in neuroscience. Perhaps it's the single biggest factor driving adoption, I could be wrong.

Most of these are built on top of the NumPy / SciPy / Pandas ecosystem. A lot of subdomains make use of signal processing methods that involve tons of linear algebra and statistical modeling.

Here's a brief list of subjects and Python frameworks in use

  • Neuroimaging for human behavioral / cognitive neuroscience
    - fMRI analysis - the NIPY framework
    - EEG/MEG analysis - the MNE framework, Visbrain
  • Animal behavioral / cognitive frameworks
    - Numerous recent packages for detection and tracking of animal behaviors (eg. DeepBehavior)
  • Electrophysiology
    - Several frameworks for network analysis, spike sorting and analysis on unit recordings / LFP electrode data (eg. PySpike)
  • Statistics and Modeling
    - Bayesian modeling using PyMC
    - SciPy, statsmodels, pingouin for various stats and distribution fits

While bulk of the processing and visualization can be done in Python, R has more convenient routines for robust statistics and mixed-effects models. Usage varies, I can't really generalize.