Over the past week I have been reading the documentation and playing with Julia’s Gadfly package. I thought it would be helpful to fellow R users coming from the world of ggplot2 to put together a quick reference guide to show the translation from one to the other. The coding and style for creating data…
In this post, I will demonstrate loading my criminal activity data into ElasticSearch sot it can be explored, analyzed and visualized in Kibana. For instructions on installing and configuring the Elastic (formerly ELK) Stack, see my previous post. Although this post will specially reference the crime data from my PostgreSQL database, I will include additional…
Exploring Mapping Data In a continuation from part 2a, this post will explore the spatial points datasets from my database. I need to assess what each dataset contains. To aid in the exploration of spatial data, I will demonstrate plotting spatial points. This can be a lot easier to look at this particular structure in…
Exploring Mapping Data My next exploration task is the mapping/geospatial tables in my database. I need to assess the what each dataset contains. To aid in the exploration of spatial data, I will demonstrate plotting of spatial points and polygons. This can be a lot easier to looking at this particular structure in tabular or…
This post will describe the Elastic Stack, also and formerly the ELK Stack, and its individual components. In a follow-up post, I’ll demonstrate how to get the ELK Stack up and running. What is the ELK Stack? The ELK Stack consists of Elasticsearch, Logstash and Kibana developed by Elastic. Later the company came out with…
In this post I’ll demonstrate how to get the ELK Stack up and running. Installing the ELK Stack First we will install Elasticsearch, then Logstash, and then finally Kibana. Most of the instructions are the same if you follow the official documentation (links provided below). If you follow my instructions, you’ll get the parts that…
Now we will be working with and visualizing COVID-19 data on top of our current spatial plots. To see catch up, check out these associated shapefile and GeoJSON posts. The output used used in this post comes from the GeoJSON post since it is in the desired coordinate system. The R script was simplified from…
This post is a supplemental tutorial to my initial post on Spatial Visualizations in R (Part 1) to work through processing a GeoJSON file in R from the https://www.geospatialhub.org/ for this particular example. You can work with the same GeoJSON file at the following link: https://www.geospatialhub.org/datasets/b0e0a99ec14748eeae750949c7bbb2ec_0?geometry=-123.671%2C40.158%2C-91.437%2C45.779 You can explore and tailor the API under the…
*** Updated Code on GitHub *** https://github.com/problemxsolutions/wyoming-r In this post I will be covering spatial visualizations using data from the state of Wyoming. For structure sake, I will be walking through each of the step outlined in my Analytic Methodology workflow. We will identify the sources of data, the processes to analyze and visualize the…
***This was created and valid in 2016. Data for this specific data project may no longer be current*** Data analysis is our investigation of the questions we set out to answer for our project during the planning stage. At this point we should have a good understanding of what are data contains, and various value…
