1. Download this repository onto your computer.

2. Install R.

3. Install RStudio.

4. Open RStudio, navigate to the "packages" tab in the bottom-right window.

5. In the packages tab, click "install."

6. Install the following packages:

   • RMySQL
   • tidyverse
   • shiny
   • shinydashboard
   • RColorBrewer
   • scales
   • lubridate

7. You may also need to install MySQL Workbench and its dependencies to connect to the database locally for this dashboard to work.

1. Change your working directory to the location of this repository on your computer.

   • Select the "files" tab from the same window where the "packages" tab is located.

   • This should default to your Documents folder. If your copy of the repository is in this folder, navigate to it from here.

   • If the repository is not in your Documents folder, type this into the RStudio console: setwd("path") (where path is the path to the proper folder)

   • If you navigate to the proper folder by clicking, you can set the working directory by clicking "More" in the files tab and select "Set as Working Directory"

     • You can also get the working directory path from "More" or by typing getwd() into the console.

2. Create your own "connection.R" file.

   • Just under the "File" tab at the top left of RStudio, there is an icon for creating a new file. Click this and select "R Script"

     • Or, alternatively, use Ctrl+Shift+N

   • In type this code into the script:

   library(tidyverse)
   
   conDatasource <- src_mysql(host = "host name", 
                              port = port#, 
                              user = "username", 
                              password = "password", 
                              dbname = "database name"
   )
   

   Where the host name, port#, username, password, and database name are your credentials. If you don't have this information, ask someone who does.

   • Save the script as "connection.R" since that is the file name that is used in the backend.

3. Run the dashboard

   • Open either twoInputs.R or oneInput.R (twoInputs allows you to choose a section to narrow down the list of names, while oneInput allows you to search all students enrolled in ISDS 1102 for the current semester).
   • In the top-right area of the top-left window (which shows the code and currently open files) select "Run App."
   • The dashboard might take a few seconds, but it should come up in another window.

The dashboard is currently being filtered for the current semester manually, so the betterBackend.R file will need to be updated every semester. This can be done easily by scrolling past the #import data section and changing the current semester variable to reflect what you want the dashboard to display. This variable is currently set to 2019SP, or the Spring 2019 semester. If old data is archived and the only data in the database is from the current semester, you can delete or comment out everything between # limit selection to current semester and # Inputs. You can also delete the filter referred to in the comment on line 54 of the betterBackend.R file. Also, the current dashboard is designed for a class that only has excel exercise submissions. If other submissions are added, some changes will have to be made to the submissions table or chart (the filtering and order of the exercise is currently determined by the excel exercise number).