Hi Rachael, overall you have really effective code that correctly computes the Pearson Correlation coefficient directly! As we discussed last Friday, it also needs to be edited so that the p-value is computed as well. Here are some notes for improving the code.
Headings and subheadings that separate each section into logical blocks of code.
A description of what's happening.
Code block
For file names, try to not use spaces in the names. This is generally good software dev practice, as spaces are something that aren't ignored in the command line and most programming languages.
I have included an example of how your code can be written up (as MET2GCP_CORR.upynb, and you can use that as a reference for your future notebooks.
Feel free to check that file out. When you're done adding the code that computes the p-value, you can merge your code with the master branch by pressing the green button!
Hi Rachael, overall you have really effective code that correctly computes the Pearson Correlation coefficient directly! As we discussed last Friday, it also needs to be edited so that the p-value is computed as well. Here are some notes for improving the code.
For all notebooks, write it up just like you would a paper (using Markdown - resource here: https://www.markdownguide.org/cheat-sheet/). This includes objects like:
# {TITLE}**Author**: {INSERT NAME}For file names, try to not use spaces in the names. This is generally good software dev practice, as spaces are something that aren't ignored in the command line and most programming languages.
I have included an example of how your code can be written up (as
MET2GCP_CORR.upynb, and you can use that as a reference for your future notebooks.Feel free to check that file out. When you're done adding the code that computes the p-value, you can merge your code with the master branch by pressing the green button!