Public Group active 2 weeks, 2 days ago

PUG – Python User’s Group

Python User’ Group (or PUG for short) is an open and informal collaborative space for experimentation and exploration with the Python programming language. It is an opportunity for those interested in Python to work together virtually and find support. Whether you are looking for advice or assistance with new or current projects, looking to discuss and learn new skills using Python tools, or to join us to play around with our collection of sample datasets, PUG is your place!

PUG is open to people of all skill levels, disciplines, and backgrounds. Complete beginners to Python will find a place here. Come, and let’s learn together.

Join PUG Slack here: https://join.slack.com/t/pug-world/shared_invite/zt-iube7uch-nVkvtIyIbpaqtQSZcMB2Ig

PUG is cosponsored by the MA in Digital Humanities / MS in Data Analytics and Visualization programs and the Mina Rees Library.

To learn more, visit http://cuny.is/pug

Admins:

`Mapping User Group Group Sessions – Spring 2023

  • Hi, everyone.

    As we prepare to begin our biweekly meetings for the Mapping User Group during the spring semester, I would like to get your feedback on what times would be best for us to meet, and what topics we should cover. I believe over the past semester and on DRI, we had attendance from a few people that have ongoing mapping projects, so I believe these working sessions could be very helpful if we focus on very concrete skills and goals in each. I am planning on bringing one tutorial/script per session, that we can go over to learn new GIS tools. I am also inclined to move more into using R for mapping, since it fits well with the need that most of us have in our project: merge our own data that we generate in our research with existing spatial data in order to create maps. My initial thoughts on possible tutorials in R for our next meetings are: 1) using ggplot and sf package for basic mapping (focusing on tools to customize our maps); 2) using the SF package functions to perform geoprocessing of vector data; 3) using the raster and rayshader package to visualize Raster data; 3) using tidyverse to manipulate both our data and vector files to create new spatial files for mapping; 4) combining packages to simultaneously analyze vector and raster data in R; 5) create interactive maps using the leaflet package in R. As usual, feel free to suggest other topics for us to cover.

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