Posts

Setting the scene for automation In the previous post I wrote about how to spin up a EC2 instance with Rstudio server, so some of the more computational heavy R processing can be moved on AWS infrastructure.

I use a Thinkpad from 2015 for my day to day work, and you can imagine things are getting slower as time goes by. Recently I had to test some computation in an R package I am developing and my computer froze multiple times.

One of the ways for getting Google Analytics data in R is using the excellent package googleAnalyticsR. GA4 and Big Query But suppose you are curious about trying (the new) GA4 because the old one is going away, and you set it up on your site (like I did on the Discindo blog).

After building a demo in Shiny for Python I decided to see how to build a demo dashboard with the other tools available for Python, namely Streamlit and Dash. The good thing about doing all these in Python is that so much of the code can be reused.

After spending few years writing R Shiny apps with {golem}, the first thing I thought about when writing the Python Shiny demo was is it possible to convert it to a python package and if yes how to it.

In the previous post I outlined the approach to query data from Wikidata, and wrangle your way to a result about some relationships between politically exposed persons on the example of the rather poor data available for North Macedonia.

Some time ago I was doing a demo for querying Politically Exposed Persons from Wikidata. This was supposed to be a part of a bigger project which didn’t materialize. Nevertheless the code can be a good exercise in the topic, so I am sharing it for anyone that might be curious.

In recent weeks, I have been trying to learn more about using the {paws} software development kit to interact with Amazon Web Services from R. So far, my focus was on the basics of DynamoDB.

blast and BlasterJS I recently learned about a really slick JavaScript component for interactive visualization of NCBI’s blast output. BlasterJS (Website, Paper) makes it possible to visualize blast results in a way similar to the typical viz available on NCBI’s website.

In our previous post we covered some basics of using the paws SDK to interact with AWS DynamoDB from R. We wrote a few simple functions to prepare R lists in the appropriate format for DynamoDB and some wrappers to put these lists as items in the remote NoSQL database.