Weathering the Pandemic

Helene Meyers on How small liberal arts colleges can best weather the pandemic (opinion):

Small liberal arts colleges focus on low faculty/student ratios and small classes that allow meaningful mentoring relationships with faculty members as well as peer education. What if a British-style tutorial were part of every first-year student’s experience? Among smaller groups, meetings powered by Zoom can foster intellectual community, while online discussion forums can require students to respond to one another’s writing. Many faculty members at liberal arts colleges have the pedagogical chops to do this work well. Colleges that can clearly communicate that such high-quality experiences can be expected in person or at a distance are more likely to be able to recruit an incoming class.

Intensive research seminars where faculty-guided independent work is supplemented with a cohort of peers who can help vet one another’s projects and learn to ask (and answer) critical questions about both the research process and its products should be provided for upper-class students. This seminar could be a prelude to capstones in the major or to other high-impact experiences such as internships. Such offerings would be in keeping with and an extension of research opportunities already on offer at many liberal arts colleges.

Some students might elect to study pandemic-related topics in an effort to process the experiences of this moment. Others might need to lose themselves in a passion that seems distant from the horrors of the present. Enabling students to make their education their own is a hallmark of the liberal arts experience, and additional intensive research and writing experiences can aid emotional and intellectual development during these unprecedented times.

Liberal arts colleges should also use this moment to integrate career coaching throughout the curriculum. First-year tutorials and research seminars are the perfect places to do some of that work. The next few graduating classes will be entering a brutal job market, and we owe our students careful instruction in the development and transferability of marketable skills.

The Power of a bash Script

Every time I run it, I am delighted by how much work the bash script for the COVID dashboard works.

~ % sh ./
remote: Enumerating objects: 35, done.
remote: Counting objects: 100% (35/35), done.
remote: Compressing objects: 100% (27/27), done.
remote: Total 29 (delta 18), reused 5 (delta 2), pack-reused 0
Unpacking objects: 100% (29/29), done.
   3ad1afa..f06d614  master     -> origin/master
Updating 67b320c..f06d614
Fast-forward            |     2 +-
 live/us-counties.csv |  6395 ++++++++++++------------
 live/us-states.csv   |   110 +-
 live/us.csv          |     2 +-
 us-counties.csv      | 12803 ++++++++++++++++++++++++++++++++++++++++++++++++-
 us-states.csv        |   226 +-
 us.csv               |     6 +-
 7 files changed, 16287 insertions(+), 3257 deletions(-)
INFO    -  Cleaning site directory 
INFO    -  Building documentation to directory: /Users/johnlaudun/Developer/COVID-Acadiana/site 
INFO    -  Documentation built in 0.10 seconds 
~ %

I will admit that the dashboard is still primitive, but the idea of it was what was important at the time, and so many dashboards have popped up since then. I mostly keep running the script for a sense of the historical depth it provides.

Quick Labels with Python’s f-string

Sometimes I need a list of titles or labels for a project on which I am working. E.g., I am working with a toy dataset and I’ve created a 10 x 10 array and I want to give the rows and columns headers so I can try slicing and dicing. I prefer human-readable/thinkable names for headers, loc over iloc in pandas-speak. And this one-liner works a treat, as they say:

labels = [label{item}' for item in range(1,11)]

Done. Place it into your dataframe creation (as below) and you are good to go.

df = pd.DataFrame(data=scores, index=names, columns=labels)