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Test_Files/
Chemistry_Tools.ipynb
Data_Analysis.ipynb
Data_Basics.ipynb
Errors.ipynb
Introduction.ipynb
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Python_Worksheet.ipynb

# Programming for Chemistry Author: Oliviero Andreussi, Department of Chemistry and Biochemistry, Boise State University E-mail: olivieroandreuss@boisestate.edu Content of the project: Basic Jupyter Lectures on Python Programming for Undergraduate Chemistry Courses and Labs * **Introduction**: covers basic programming strategies, assignments, conditionals, loops, formatting, and plotting * **Errors**: covers concepts on measurement errors, some basic statistics (binomial and normal distributions), error propagation, reading files, Pandas dataframes, and linear regression with Sklearn Assignments: * **Python Worksheet**: four tasks on error analysis, basic math on a dataset, more advanced operations on the columns of a dataset, and linear regression fit. Datafiles used in the notebooks: * test.csv: absorbance vs. time data collected in a kinetic experiment * protein.csv: atomic properties (element, environ descriptors, coordinates, mass, distance from center of mass) of atoms in a small protein

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