The purpose of this extra credit assignment is to use the Python (computer programming language) to generate a lab report.  There is a maximum of 2 extra credit "percent" points in the fall semester.

 tutorial / assignment

set-up:   readme   (*.docx file)

brief Python tutorial / assignment:   *.ipynb file  --  down load file (i.e. right click mouse (on link to *ipynb file) --> Save link as . . . --> Save (onto your desktop for ease of finding it) -->  goto Juypter (or google colab) --> upload the file), then open the file using the Jupyter notebook,  JupyterLab,  or Google colab.  read the *.ipynb file for more information about the extra credit assignment.   

the purpose / goal of using the (FREE) Python computer programming language 1 and (FREE) Juypter notebook (or JuypterLab or Google colab), an interactive development environment (IDE ), for Python (and other computer programming languages), is to introduce you to Python and a notebook interface, which you can use to prepare your lab report and is a potentially powerful tool in an education 2.

Using the Juypter notebook emulates three separate software (Word, Excel, and Mathematica), so its use can simplify the preparation of your lab report and could replace a calculator in solving tedious homework problems using its computer algebra package / library, sympy.  

Furthermore, the assignment may be of value to future STEM majors as you might use such tools in college 3 and you would develop your life-long learning skills as you use the internet to learn about using the Jupyter notebook and Python.

The preceding *.ipynb file was developed with the Juypter notebook IDE and the instructions in the above assignment are based on the Juypter notebook IDE.  Do not anticipate there to be a significant difference between the Juypter notebook versus JuypteLab.  While the Google colab website has a similar user interface as the Juypter notebook and both use Python, there are some differences 4.


1 python tutorials; e.g. scipy lecture notes; Python for scientific computing; Intro to scientific computing in Python

2 e.g.  Caltech 2018;  UCB 2017;  Barba et al 2019;  UCAR atmospheric science

3 e.g.  Python / Juypter (20202021);   Python / google colab (2021);  SageMathCell;   Rstudio

e.g. (i) using the "solve" command from sympy, the output will be in LaTex, so select, copy, and paste into a "text"  (i.e. Markdown) mode cell, then press "Run" to express your answer, (ii) embedded images in Juypter notebook can't be seen using Google colab, and (iii) the colab has a real-time collaboration feature



video   (@ ~ 3:40) with quote:  "Most scientists think of programming as a  tax they have to pay to do science ". 

article:  claims that python is a relatively "easy" computer progamming language to learn.