Four guided notebooks under notebooks/getting_started/ aimed at someone new to Python and data science. The series progresses: project orientation → Python/pandas crash course → exploring one tracking DB → first trained-vs-naive comparison using load_roi_data + Mann-Whitney U. Each notebook leans heavily on markdown explanations, includes exercises with empty cells, and links out to canonical references (JupyterLab, official Python tutorial, pandas 10-min guide, Wikipedia for stats concepts). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
15 lines
596 B
Markdown
15 lines
596 B
Markdown
# Tutorial notebooks
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Read these in order:
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1. **`00_welcome.ipynb`** — what's the project, where the data lives,
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how to use a Jupyter notebook.
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2. **`01_python_pandas_basics.ipynb`** — minimum Python and pandas you
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need to read project code.
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3. **`02_explore_one_database.ipynb`** — open one tracking DB, plot a
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trajectory, compute a single distance.
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4. **`03_compare_trained_vs_naive.ipynb`** — first real analysis,
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comparing groups.
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After these, the notebooks one level up (`flies_analysis*.ipynb`) walk
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through the full analysis pipeline that the previous student built.
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