Skip to content

Home

Jump to bottom
Erika Austhof edited this page Dec 5, 2022 · 19 revisions

Welcome to the LearningDataScience wiki!

This Wiki is for the Roots for Resilience Research Assistantship. Learn more about Roots for Resilience from the UArizona Data Science Institute.

Tasklist

  • Run weekly analysis
  • commit data and output folders to repo for collaborators
  • commit GitHub code to repository for collaborators, add relevant climate data and code
  • pull monthly climate data from PRISM, re-merge and re-run analyses
  • work on the README for the repository
  • work on AZ and NM results
  • summarize initial results for CO team
  • work on presentation for symposium
  • See if python-climate-indices would be a good option for getting drought data for thesis project
  • Determine a project to use for the R for Reproducibility workshop, maybe the Rain analysis?
  • Write a function to merge PRISM data, maybe a loop?
  • Cyverse Intro Training

Updates

  • 11/30/2022: This past week I did my presentation for my lab group. We had a great discussion about open science in public health, considerations for health data, and how we might integrate these concepts into future work within our lab. Our lab was interested in working on a collaborative project in the future and doing it all within R and GitHub - that was a big win!

Previous Updates

  • 11/23/2022: This past week I worked on my presentation for my lab group, prepping for the final presentation for R4R. I also FINALLY got my weekly data to run! I shared those results with my committee chair this week.

  • 11/16/2022: This past week i have been working on presentations for collaborators and running the monthly models for outputs. I discovered an error in my monthly code which was providing inaccurate results, since that's been fixed I was able to re-run the analyses and summarize the information to a R Markdown document for each state. I'll update these documents and commit them to the repo as we go.

    • Issues: I am still having problems with merging by week, but after discovering the lubridate package I think that will take care of the majority of the issues I'm having.
    • Takeaways: It's interesting to learn that some of the base R functions aren't considered the normal functions to use, for example I was using the string to frame function in R to gather date information, but the lubridate package is actually considered the standard. It's a good learning experience for me to check for packages before trying to hard code anything in R first. Working on the FOSS presentations was great to learn from the other students working on repositories from their project. I am excited to hear more from the other groups on Thursday.

  • 11/9/2022: This past week I had a few presentations with collaborators and I was able to show them a first iteration of the GitHub repository. They had some helpful feedback to share so I am working on integrating that.

    • Issues: I attended R office hours and got some support for my code. I am still running into issues with merging, but I hope to get that figured out this week. I was also struggling to understand how containers would work with PHI, but the session yesterday and the content shared from Heidi was really helpful!
    • Takeaways: Having the feedback from my collaborators was really helpful in thinking through the preliminary results, and in moving forward with developing the compendium for them. I am hopeful that it will be used by them more frequently now that they have seen it and how it works.

  • 11/2/2022: This past week I presented initial results to my CO collaborators and am working on the code and repositories for the other states. I also scheduled my department talk for R4R and am working on that PPT too.

    • Issues: I'm having some trouble aggregating my code to weekly level. I'm going to the R drop-in hours next week for some support.
    • Takeaways: I really appreciated seeing everyone in person on Tuesday! It was nice to see how our research might overlap and meet the whole data science team in person. I am learning a lot from the FOSS workshops with all the additional resources they share in the modules.

  • 10/26/2022: This past week I presented my progress on my project for R for Reproducibility, which is also the same project I'll use for R4R. I am developing a research compendium for my collaborators to submit code and data changes to in GitHub, and use it for future manuscripts and reports.

    • Issues: None to report this week, I am making good progress!
    • Takeaways: The FOSS workshop on reproducibility in GitHub was a lot of what I learned in the R workshop, but focusing more on the command line. I prefer to use the terminal in R for my GitHub connections since I'm already working in R but it's nice to know there are other options. I also really appreciated meeting Carlos and Jordan in person for dinner and getting to learn more about their careers and studies.

  • 10/19/2022: This past week I played catch up with the FOSS workshops, and finished my R for Reproducibility project. I will share results from that tomorrow in our Thursday session. This project was the beginning of the project I'll be using for R4R, creating a GitHub repo for my collaborators across 4 states.

    • Issues: Since I am using health data, I am wary about putting all of the data in GitHub, even though it's a private repository. I am trying to figure out what I can share, and what I can't, but still make the project reproducible for the states.
    • Takeaways: The FOSS workshop on Git and GitHub using the terminal in Cyverse was really helpful. Since I knew how to do that in R already, this helped solidify my learning and teach me something new!

  • 10/12/2022: This past week I set up a repo for my thesis project and collaborations and began working on a README and file structure. I invited my first collaborator into the GitHub who was interested in how it gets set up. I am using R to push and pull changes to the repo.

    • Issues: This week I am trying to find the balance between documentation and progress on the project. I spent much more time documenting and less time on actually doing the project, so I'm hoping to get more done next week!
    • Takeaways: Using R to push changes to GitHub is not as difficult of a task. As long as I continue to use those skills, over time I think it will be easier to remember the code and not have to look it up each time. I am also really really thankful for all the people supporting me on my thesis project, so many collaborators have helped to get it up an running!

  • 10/5/2022: This past week I attended an API for scientists workshop which was really great. I also turned my main thesis project into a GitHub repository and shared it with my collaborators. We're going to start working on R code together. I also explored README templates, folder project template structures, and best practices for data management plans. I also helped guide a project that I'm on in some better data management practices we could implement for the project.

    • Issues: I don't have any issues this week - I am really excited about learning all these new tools and implementing them in my work!
    • Takeaways: Having a base understanding of an API was really helpful in order to know how to use them. The python-climate-indices, as well as the CRan prism project both use APIs but I didn't previously understood how they worked, so coding was difficult; now I feel like I could try it again with more success.

  • 9/28/2022: This week we discussed project management in the FOSS workshops. I really liked the idea of a binding document for a project that details expectations, who is doing what, and the goals/objectives for a project. I was really intimidated about the research object...it seems like a massive project that would take a long time to complete. I'm hoping with the FOSS workshops we'll get more understanding of how to do this type of work in the future.

    • Issues: This week I'm having issues with getting all the health data I need for my project, working through data use agreements, IRB applications, and working with partners to get data at a level that makes sense. We are making slow progress!
    • Takeaways: I merged all of the data for my project with CO and cleaned up my R code so that my filepaths are relational, rather than hard-coded to my own folder. I am planning to turn this R project into a GitHub for my collaborators to provide comments on my code as well!

  • 9/21/2022: This week we started the FOSS workshops and discussed open science. I also attended the Reproducibility in R workshops where we learned about branches and forking in GitHub and overall project management using git and GitHub.

    • Issues: This week I am having issues with pulling in multiple datasets offline and merging them in R. Since I'm working with large datasets of climate data, I've figured out how to do it manually, but it takes awhile, and I'd like to learn how to do it more efficiently.
    • Takeaways: I am seeing how I could use R for my thesis work more clearly. I like the idea of setting up a private repository for my collaborators across states so that we can work together on code and data.

  • 9/14/2022: This week I set up my notebook for the R4R cohort, and this is the first edition of the notebook for the 9/14 deadline. Feel free to navigate the pages on the right, and see updates down below for my learning progress so far.

  • 9/8/2022: This week we started the pre-workshop for FOSS, and learned about the differences between open science and FAIR principles. Check out the associated new pages for: Docker, FAIR principles, and FOSS workshops for learning activities.

    • Issues: I am still unsure how I will use Docker in my own work, but am excited to learn more as FOSS continues.
    • Takeaways: I was excited to learn about data standards in public health, and I am getting more comfortable with navigating GitHub!

  • 9/1/2022: This week I reviewed the lectures from previous sessions and got my computer set up for RStudio and GitHub.

    • Issues: R programming is still new to me, but I am working through a self-paced course to help with coding skills.
Clone this wiki locally