CS 424 Project 2

Project 2 will be an individual project to give people some more practice with writing a web-based application that visualizes data in multiple ways using R and Shiny and ggplot2 and leaflet. In this project we will add plotting the geographic locations of data based on their latitude and longitude and displaying that data in different ways on maps.

This project will again focus on using R to visualize data on electrical power generation in the US, and use shiny to give people an interactive interface to create those visualizations. In Project 1 we looked at the US as a whole and at different states to see how they were different in their energy mixes. Here we are going to dive inside the state boundaries to look at the actual locations of the different plants and allow us to see how geographic as well as political boundaries affect coal / gas / solar / hydro / etc energy production in the US.

The original data is available from https://www.epa.gov/egrid/download-data

in particular this file: eGRID2018v2 Data File (XLSX)

where we will be looking at data from the PLNT18 tab.

and we will also be making use of some of the historical files in:

Download all eGRID historical files (1996-2016) (ZIP)

such as the eGRID2000_plant.xls file and its EGRDPLNT00 tab.

For this assignment you can make changes to the data files before you load them into R, and you very likely should make some changes to shrink the size of the data files. You need to clearly document how you modify the files in your website to the extent that someone following your instructions could recreate your files from the originals.

The columns from the 2018 data that are most of interest to us are:

plant state abbreviation
plant name
plant latitude
plant longitude
11 columns showing the annual generation from different sources

(as plants can have more than one source)

COAL, OIL, GAS, NUCLEAR, HYDRO, BIOMASS, WIND,

SOLAR, GEOTHERMAL, and then you can combine the last 2 into OTHER

giving you 10 columns total

From these columns you can compute the data for other columns

- percent of total for each of the 10 types

- total renewable (HYDRO, BIOMASS, WIND, SOLAR, GEOTHERMAL)

- total non-renewable (the others)

- percent of total that is renewable

- percent of total that is non-renewable

Going further into the project you will need to grab data from 2000 and 2010.

Once you convert the raw data files into the files you plan to use I would again suggest playing with the data in RStudio or Jupyter to try out various manipulations and visualizations before creating the user interface in Shiny.

We will be using Leaflet for the mapping this time instead of usmap.

Again you will be writing your code to run full screen in a web browser at 1920 x 1080 resolution and it should run on all current browsers (Chrome, Safari, Firefox, Explorer, Edge, etc.). The fonts and visualization primitives you create should be work effectively at that scale. The user should never to scroll the window, ever, so you should experiment with different ways to organize the information and controls to find the most effective combinations. Users will be using a mouse / trackpad to interact so make sure your controls are reachable and at an appropriate size.

For 40% you need to:

read in your 2018 data file and create an interactive visualization in R and Shiny on Shinyapps.io that initially shows a properly centered and scaled leaflet map of the state of Illinois showing.

location of all of the power plants in Illinois colored by type
set of check boxes, one for each energy source, plus 'all' (where all is the default selection), renewables, and non-renewables, allowing the user to filter which energy sources are shown on the map
map is pannable and zoomable with the plant locations updating dynamically
map has a reset button to go back to the original view
be able to handle plants with multiple types of generation at the same location
legend showing which type of plant is which color
colors are appropriate for the map
have an 'about page' in your app with appropriate credits

For an additional 30% you need to the ability to compare 2 states over three different years

read in your 2000, 2010, and 2018 files and create a split screen visualization capable of showing two independent leaflet maps. The left should initially show the location of the plants in Illinois in 2000 and the right should show the location of the plants in Illinois in 2018 (as in the part above)
identical set of check boxes to independently show the power sources in each map.
ability to link the check boxes to affect both maps simultaneously
ability to choose a year (2000, 2010, or 2018) for either half of the screen
ability to choose a state from a dropdown menu of the 50 US states (again using the long names like 'Illinois' rather than IL) for either half of the screen - choosing a state should automatically pan and zoom the map to show a proper view of that state.
in addition to showing the location and type of each plant the size of the marker should show its generation capacity (larger markers for larger generation capacity)
allow the user to choose from 3 different useful leaflet map types
clicking on a marker shows the plant name, and its generation capacity (for the different types it has), the percent of the total capacity that is renewable, and the percent of the total capacity that is non-renewable
the color for each power source should be consistent across all the visualizations in your interface
each map is pannable and zoomable with the plant locations updating dynamically
each map has a reset button to go back to the original view

For an additional 30% you need to allow the user to see the entire US at once

in addition to each of the 50 states the user should be able to pick the entire US and see an appropriately panned and zoom map showing the continental US by default (i.e. Alaska and Hawaii can be out of view to start)
the map is pannable and zoomable with the plant locations updating dynamically
the map has a reset button to go back to the original view
same set of check boxes to independently show the power sources. This time by default none should be selected.
same ability to show 2000, 2010, or 2018
allow the use to filter by generation amount with two sliders. The user should be able to use this control to show the big power plants ( > n MWh), the small ones ( < n MWh), or a set in between. By default 'all' should be selected.
This one could show a lot of markers so you will need to do some optimizing.

Graduate Students need to add:

Allow the user to display which plants were added or idled in 2010 and 2018 compared to the previous dataset. The ORIS facility code will be very helpful.

Note that as the map data is (reasonably) current it may not exactly match the situation in any of those three years, especially in terms of what buildings are where.

Whenever the user interacts the interface should respond quickly and appropriately.

In all of these case you need to make sure that your visualizations are well constructed with good color and font choices, proper labeling, and that they effectively reveal the truth about the data to the user.

Note that as part of the web page part of the grade you will need to use your interface to show your findings, so make sure that the way your interface displays information is clear.

Turning in the Project

There are two due dates for the project.

The source code and application are due first.

For this project you should host your solution using Shinyapps.io.

Your code should be turned in and made available on GitHub ( https://github.com/) in a public repository for the project. You can keep the repository private while doing your development. I would suggest setting up the GitHub project early and regularly pushing code to it as a backup.

It is important to note that 'getting it to work' is just a prerequisite to using the application to find answers to your questions. It is that usage that will give you ideas on how to improve your app to make it easier and more intuitive to find those things. Writing the application at the last minute pretty much guarantees that you will not come up with an intuitive interface.

Before the application due date&time please send an email to andy and abeer with the URL of your GitHub site and your Shinyapps site.

The second deadline is for the documentation which should be part of the web page you created at the beginning of the course.

This page should have several sections including:

link to your visualization solution
1 page worth of text on an introduction and a description of how to use your application and the things you can do with it.
1 page worth of text on the data you used, including where you got it, what you did to it.
link to your project on GitHub giving access to your well commented source code, any necessary data files, and any instructions necessary to run it. These instructions should start from the assumption that the reader has a web browser on their computer and tells the user everything else he/she needs to know and do to get it running using R studio, including installing correct versions of all the required software.
1 page worth of text on what interesting things you found about the data using your application.

all of which should have plenty of screenshots with meaningful captions. Web pages like this can be very helpful later on in helping you build up a portfolio of your work when you start looking for a job so please put some effort into it.

You should also create a 5 minute YouTube video showing the use of your application including narration with decent audio quality. That video should be in a very obvious place on your web page. The easiest way to create the video is to use a screen-capture tool while interacting with your application, though you will most likely find its useful to do some editing afterwards to tighten the video up. If you do decide to use your phone or tablet to make the video, then please shoot the video in landscape rather than portrait orientation. Your video should show the capabilities of your tool through a set of specific examples of interesting things you found in the data.

I will be linking your web page to the course notes so please send andy and the TA a nice jpg image of your visualization for the web along with the link to your website before the deadline. The image should be named p2.<your_last_name>.<your_first_name>.jpg and be roughly 1920 x 1080

Once you have your web page done, send the URL to Andy and the TA before the deadline. We will respond to this email as your 'receipt'.

An important part of creating these kinds of applications is getting feedback and using it to improve your design, and learning to give quality feedback to others.

Normally we would be spending time in class for each person to show off their work and get feedback. This term we will be doing this asynchronously. See the course notes for week 10 for more details.

Agrawal, Piyush	GitHub	Shiny	Web	Video
Baez, Brian	GitHub	Shiny	Web	Video
Bhatt, Vivek	GitHub	Shiny	Web	Video
Chen, Yi-Chun	GitHub	Shiny	Web	Video
Davidson, Will	GitHub	Shiny	Web	Video
Ghuneim, Matthew	GitHub	Shiny	Web	Video
Gonzales, Joshua Luis	GitHub	Shiny	Web	Video
Ibtasar, Rabia	GitHub	Shiny	Web	Video
Johnson, Amal	GitHub	Shiny	Web	Video
Khandwala, Herrit	GitHub	Shiny	Web
Kohli, Paras	GitHub	Shiny	Web	Video
Kolakowski, Pat	GitHub	Shiny	Web	Video
Lee, Ting-Shao	GitHub	Shiny	Web	Video
Mach, Khang	GitHub	Shiny	Web	Video
Mara, Valo	GitHub	Shiny	Web	Video
Mendoza-Avila, Hilda	GitHub	Shiny	Web	on web page
Mo, Jiajun	GitHub	Shiny	Web	Video
Modi, Hiral Mahesh	GitHub	Shiny	Web	Video
Perez-Serna, Jesus	GitHub	Shiny	Web	Video
Raza, Syed	GitHub	Shiny	Web	Video
Repta, Jonathon	GitHub	Shiny	Web	Video
Reyes, Yazmin	GitHub	Shiny	Web	on web page
Shumway, David	GitHub	Shiny	Web	Video
Suraminitkul, Eakasorn	GitHub	Shiny	Web	Video
Tapia, Andres	GitHub		Web	Video
Ziminski, Matt	GitHub	Shiny	Web

last revision 3/30/2021 - fixed some grammar issues

Project 2 - Raw Power