Monday, September 15, 2025

Python script visualization tools

 since your journal wants you to produce clean figures, you’ll need a reliable way to run the Python script and export the visuals as high-resolution images (PNG or PDF). Here are a few practical options you can use right away:


🔹 1. Google Colab (Free, Web-Based)

  • Just open Google Colab with your Google account.

  • Create a new notebook, paste in the code I provided, and run it.

  • Figures will render directly in the browser, and you can save them as PNG.
    Best choice for quick, no-installation plotting.


🔹 2. Jupyter Notebook (Local)

  • Install Anaconda or Jupyter via pip.

  • Run the notebook locally (jupyter notebook in terminal).

  • Great if you want offline control and the ability to tweak figure formatting.


🔹 3. Kaggle Notebooks (Free, Online)

  • Log in to Kaggle, go to “Code,” create a new notebook.

  • Paste the script, run, and download figures.
    Good if you’re already using Kaggle datasets or working in research teams.


🔹 4. Deepnote / Noteable (Collaboration-Oriented)

  • Both are browser-based notebooks like Google Colab.

  • Useful if you need to co-edit with collaborators.


⚠️ Important: When exporting figures for journal submission, make sure to:

  • Save as .PNG at 300 dpi or .PDF (vector, best for print).

  • Keep consistent font size (10–12 pt) and labels.

  • Use APA-style captions (I can draft them for you next).

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