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Scientific Computing for Chemists text for teaching basic computing skills to chemistry students using Python, Jupyter notebooks, and the SciPy stack. This text makes use of a variety of packages including NumPy, SciPy, matplotlib, pandas, seaborn, NMRglue, SymPy, scikit-image, and scikit-learn.

Jupyter Notebook 100.00% Python 0.01%
chemists nmrglue scipy numpy python jupyterlab jupyter-notebooks chemistry computing scientific-computing

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scicompforchemists's Issues

6.2.2 Weighted Averages

Thank you for this great resource!

I think there is a small error in the Weighted Averages section (pg 182) the equation is divided by 5 but I think this should be 9 (and in fact the python code uses 9 so I think the actual python code is correct).

Thanks again.

This is AWESOME

This is super awesome Charles - You ROCK!
and under a CC license

Great job - you are winning!

Incorrect element data in Chapter 10

I'm not sure where the element data for chapter 10 came from, but Tl-Rn are incorrectly categorised as d-block elements. As I'm sure you know, they should be p-block elements. I wouldn't have noticed if the graph in the chapter didn't show a d-block gas (see attached graph from Chapter 10.3.5)

If you left it incorrect intentionally for demonstrative purposes, it may be worth leaving a note saying as much. Otherwise, if you like I can submit a PR and fix it up?

image

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