All posts

  1. 🔗Nesting Json and Using Template Literals to Produce HTML

    I come from the R world working with data. A very common data analysis technique is to take data and group it by a variable. I wanted to do the same thing with javascript and then append the data using .innerHTML to the DOM. I am working on an app that has data that I would like the user to be able to display in various different ways. I had a really hard time finding any information on grouping data and how to loop through the grouped data to display the grouped data in HTML. I am not very good a javascript so this was quite a challange for me.

  2. 🔗D3js River flows

    I'm working on a website for a rafting non-profit. I thought it would be cool if they could display the flow data for local rivers. I also thought this would be good time for me to learn more about D3js and the USGS instantaneous flow data API.

  3. 🔗Django Relationships

    For some reason, in the winter I get the urge to learn something new. This year, I'm attempting to pick up Django again (gave an effort a year ago too). One of the things I wanted to better understand is how to implement database relationships.

  4. 🔗Colorado: Hex Plots, APIs, and D3js

    After my last blogpost I was a little frustrated at how poorly the title text resized using ggplot and ggsave. It was a minor issue to be honest, but I figured I could learn something new by exporting the data as geojson and plotting it using D3 js. So here it goes.

  5. 🔗Colorado: Hex Plots, API packages, and R

    image

    I've been seeing a lot of hex plots made with r. They are a way to semi-artistically visualize spatial data. Although I don't think this is completely appropriate for most visualizations, it looks amazing. Here are a few examples of how I made hex plots in R.

  6. 🔗Spatially Balanced Sample Designs in R with `spsurvey::grts()`

    We've been using spatially balanced stratified study designs more frequently at work these days. They are a good way to make probabilistic inference over large areas. A popular method of creating these designs is using the R function spsurvey::grts(). The following is a basic (very basic) explainer of how to get up and running with grts() function and what it is. But a bit about GRTS and spatially balanced study design before we get coding.