Redmine

I've release a new dataset that pre-sums the pixel values in buffers and rings around each SEZ:

https://data.sandiegodata.org/dataset/sandiegodata-org-sez-lights/

There is also an example analysis notebook that shows you how to use the data:

https://github.com/sandiegodata-projects/chartercitiesinstitute.org-sez/blob/master/notebooks/ericbusboom/05%20Mean%20Lights%20File.ipynb

This dataset will allow you to analyze the features that are related to SEZ economic growth without doing an of the geographic processing that has been difficult to get the environments configured for.

I re-created the conda environment files, with two files, one for Macs and one for Linux. See the README for the repo for details:

https://github.com/sandiegodata-projects/chartercitiesinstitute.org-sez

If you are on windows, see the requirements/build.sh file, which shows the process for bootstrapping the conda environment. Basically, you load a minimal environment, pip install some more modules, then export the environment spec to a file. If you create an environment for Windows, please add it to the requirements directory.

eric.

I updates the conda environment config and verified that my notebooks run with a fresh install, so you should be able to checkout the repo and follow the setup instructions in the README:

https://github.com/sandiegodata-projects/chartercitiesinstitute.org-sez

I've just published a blog post about the project and kickoff meeting, with a few neat images from early analysis:

https://www.sandiegodata.org/2021/07/economic-development-from-nighttime-lights/

Here is our Zotero research library, which you should be able to read without an account. But, you will need an account to add papers -- email Eric for help.

https://www.zotero.org/groups/3865474/special_economic_zones/library

Here is the meetup for the project kickoff.

https://www.meetup.com/San-Diego-Regional-Data-Library/events/279241185/

I've added pages to the Wiki for useful datasets and basic ideas about the direction of the project.

https://redmine.civicknowledge.com/projects/sez-analysis/wiki

Mariel shared with me a set of files, from which I've extracted a subset that has students for 2016-2017 and 2017-201 at a few schools, with their GPA 1 and GPA 2. This looks like it will be the main set of data to analyze. Here is the combined file:

https://docs.google.com/spreadsheets/d/16ENWTVx4c_IuQqYDpMVLGIslnSuI9wZF6adK3qO6gHg/edit?usp=sharing

If this is the right set of data for the Challenge Assemblies, I'll start cleaning it.

I'm trying a new way of handling data questions, the Insights website. The water-project tag identifies questions specific to this project, but there are also questions on the site that are not part of the project. Feel free to comment on or answer any of them.

I'll be promoting this site to journalists, nonprofits and other who are interested in getting data answers, and I hope that you'll follow the questions and answer some of them. You can get immediate notification of new questions and answers from the Slack channel.

After the next meeting, I'll probably move the Water quality project into this format; rather than having meeting dedicated to just water quality, we'll have Data Library meetings that are focused on answering a few of the open questions.

Please visit the site and review a few of the questions in with the water-project tag, and if you have analysis, link them in as answers. If you are working on an analysis that is different from the current questions, you can create and answer your own question. Just be sure to apply the water-project tag.

We've got a new dataset for the San Diego Coastkeeper water monitoring program. This data comes from CEDEN, so it has the same format as the Beachwatch bacteria counts, but also includes measurements for temperature, pH, turbidity and nutrients.

https://data.sandiegodata.org/dataset/ceden-waterboards-ca-gov-sdck_monitoring

I've extracted all of the measurements stations from this dataset and added them to the Beachwatch stations, to produce this map:

http://water.sandiegodata.org/maps/stations/

You can get the link to the map from the main webpage for the project:

http://water.sandiegodata.org