Our philosophy

We at Trend CT believe in open data. Our scripts may be too technical for the average reader, but we make it accessible because we believe it is important to be as transparent as possible about our methodology so our work can be checked or expanded upon.

We strive to achieve a few things with our repos: Downloading and running the code as instructed will produce the data and exploratory charts used in our stories The data itself will be an easily found location in the repos for those who don’t care about the transformation or analysis process Our scripts will be clearly documented and can serve as a way for readers to learn advanced data analysis techniques

We encourage visitors look over our calculations and expand upon our analysis or inspire you to create new visualizations.

The stories we write are usually Connecticut focused but since we use national data it’s not difficult to tweak a line in our scripts to generate an analysis for a different state.

Note: Our data used to be in a folder within our projects Github repo TrendCT, but we moved that into a new org repo TrendCT-Data. We’re in the process of fixing links in our stories.


The data is available under the Creative Commons Attribution 4.0 International License and the code is available under the MIT License. If you do find it useful, please let us know.

If you use our data or methodology, please give us a shout out in your story. It’d also be nice if you gave the author of the story a heads up.

Check us out on Twitter @TrendCT and on Facebook/TrendCT.

Data Stories Repos

Common Questions:

  • What’s a repo?
    • Short for “repository”, a digital directory where we store (and you can download) files for our projects.
  • How am I supposed to download the files?
    • You can download individual files through our repo or just clone/download the entire project.
  • How do I work with the data in the repo?
    • It depends! If the files are R, then you’ll need R and RStudio first. We wrote up how to get started with R.
    • Otherwise, the code’s in Python, which we’ve also written about how to get started with.