Added vignette

Description

@@ -1,5 +1,5 @@
 Package: eAnalytics
-Version: 0.1.0
+Version: 0.1.1
 Title: Dynamic Web-Based Analytics for the Energy Industry
 Description: A 'Shiny' web application for energy industry analytics.
       Take an overview of the industry, measure Key Performance Indicators,
@@ -9,7 +9,7 @@ BugReports: https://github.com/paulgovan/eanalytics/issues
 Authors@R: person("Paul", "Govan", email = "pgovan1@aggienetwork.com", role = c("aut", "cre"))
 Depends:
     R (>= 2.10.0),
-    plotly,
+    plotly (>= 3.6.0),
 License: Apache License
 LazyData: TRUE
 Imports:
@@ -22,3 +22,6 @@ Imports:
     shiny,
     shinydashboard
 RoxygenNote: 5.0.1
+Suggests: knitr,
+    rmarkdown
+VignetteBuilder: knitr

NEWS.md

@@ -0,0 +1,6 @@
+# eAnalytics 0.1.1
+
+## Major changes
+
+* Added the ability to save data to a csv file
+* Updated upstream dependency 'energyr'

cran-comments.md

@@ -3,19 +3,7 @@
 * win-builder (devel and release)
 
 ## R CMD check results
-There were no ERRORs or WARNINGs.
-
-There was 1 NOTE:
-
-* NOTE Maintainer: 'Paul Govan <pgovan1@aggienetwork.com>'
-
-New submission
-
-Possibly mis-spelled words in DESCRIPTION:
-  Analytics (3:20)
-  analytics (4:60)
-
-* These words have the correct spelling.
+There were no ERRORs, WARNINGs, or NOTEs.
 
 ## Downstream dependencies
 There are currently no downstream dependencies for this package.

inst/app/server.r

@@ -8,24 +8,20 @@ data(pipeline, package = "energyr")
 data(lng, package = "energyr")
 
 # Aggregate pipeline data for googleVis chart
-motionData <-
-  dplyr::select(pipeline, Type, Year, Cost, Miles, Capacity)
+motionData <- dplyr::select(pipeline, Type, Year, Cost, Miles, Capacity)
 motionData <- dplyr::filter(motionData,!is.na(Year))
 motionData[is.na(motionData)] <- 0
 motionData <- aggregate(
   motionData[, 3:5],
   by = list(Year = motionData$Year, Type = motionData$Type),
   FUN = sum
 )
-motionData$Year <-
-  as.Date(as.character(motionData$Year), format = "%Y")
+motionData$Year <- as.Date(as.character(motionData$Year), format = "%Y")
 
 # Calculate the number of unique companies, projects, and facilities in database
-company <-
-  length(unique(electric[, 1])) + length(unique(hydropower[, "Company"])) + length(unique(gas[, 1])) + length(unique(storage[, "Company"])) + length(unique(lng[, "Company"])) + length(unique(oil[, 1]))
+company <- length(unique(electric[, 1])) + length(unique(hydropower[, "Company"])) + length(unique(gas[, 1])) + length(unique(storage[, "Company"])) + length(unique(lng[, "Company"])) + length(unique(oil[, 1]))
 project <- length(unique(pipeline[, "Name"]))
-facility <-
-  length(unique(hydropower[, "Name"])) + length(unique(storage[, "Field"])) + length(unique(lng[, "Company"]))
+facility <- length(unique(hydropower[, "Name"])) + length(unique(storage[, "Field"])) + length(unique(lng[, "Company"]))
 
 shiny::shinyServer(function(input, output, session) {
   # Create the projects box
@@ -69,7 +65,7 @@ shiny::shinyServer(function(input, output, session) {
     }
     plotly::plot_ly(electric,
                     x = Year,
-                    y = Rate,
+                    y = Revenue,
                     group = Company)
   })
 
@@ -102,8 +98,7 @@ shiny::shinyServer(function(input, output, session) {
       "<br><strong>Capacity (KW): </strong>",
       hydropower$Capacity
     )
-    pal <-
-      leaflet::colorFactor(c("navy", "red"), domain = c("Expired", "Active"))
+    pal <- leaflet::colorFactor(c("navy", "red"), domain = c("Expired", "Active"))
     leaflet::leaflet(hydropower) %>%
       leaflet::fitBounds(-125, 49,-62, 18) %>%
       leaflet::addProviderTiles("Esri.WorldStreetMap", group = "World Street Map") %>%
@@ -165,8 +160,7 @@ shiny::shinyServer(function(input, output, session) {
       "<br><strong>Total Capacity (BCF): </strong>",
       storage$Total
     )
-    pal <-
-      leaflet::colorFactor(c("navy", "red", "green"),
+    pal <- leaflet::colorFactor(c("navy", "red", "green"),
                            domain = c("Depleted Field", "Salt Dome", "Aquifer"))
     if (input$storageSize == "Total") {
       leaflet::leaflet(storage) %>%
@@ -241,8 +235,7 @@ shiny::shinyServer(function(input, output, session) {
       lng$Capacity
     )
     if (input$lngColor == "type") {
-      pal <-
-        leaflet::colorFactor(c("navy", "red"), domain = c("Export", "Import"))
+      pal <- leaflet::colorFactor(c("navy", "red"), domain = c("Export", "Import"))
       leaflet::leaflet(lng) %>%
         leaflet::addProviderTiles("Esri.WorldStreetMap", group = "World Street Map") %>%
         leaflet::addProviderTiles("CartoDB.DarkMatter", group = "Dark Matter") %>%
@@ -326,8 +319,7 @@ shiny::shinyServer(function(input, output, session) {
 
   # Draw a natural gas pipeline heatmap
   output$heatmap <- d3heatmap::renderD3heatmap({
-    pipeline <-
-      subset(pipeline, select = c("Cost", "Miles", "Capacity"))
+    pipeline <- subset(pipeline, select = c("Cost", "Miles", "Capacity"))
     dfcor <- cor(pipeline, use = "complete.obs")
     dfvar <- dfcor ^ 2 * 100
 
@@ -349,14 +341,11 @@ shiny::shinyServer(function(input, output, session) {
   output$boxplot <- plotly::renderPlotly({
     pipeline <- na.omit(pipeline)
     if (input$gas == "cost") {
-      cost <-
-        data.frame(Year = pipeline[, "Year"], Cost = pipeline[, "Cost"])
+      cost <- data.frame(Year = pipeline[, "Year"], Cost = pipeline[, "Cost"])
     } else if (input$gas == "costMile") {
-      cost <-
-        data.frame(Year = pipeline[, "Year"], Cost = pipeline[, "Cost"] / pipeline[, "Miles"])
+      cost <- data.frame(Year = pipeline[, "Year"], Cost = pipeline[, "Cost"] / pipeline[, "Miles"])
     } else if (input$gas == "costCap") {
-      cost <-
-        data.frame(Year = pipeline[, "Year"], Cost = pipeline[, "Cost"] / pipeline[, "Capacity"])
+      cost <- data.frame(Year = pipeline[, "Year"], Cost = pipeline[, "Cost"] / pipeline[, "Capacity"])
     }
     plotly::plot_ly(cost,
                     y = Cost,

vignettes/eAnalytics.Rmd

@@ -0,0 +1,93 @@
+---
+title: "eAnalytics: Dynamic Web-based Analytics for the Energy Industry"
+author: "Paul Govan"
+date: "`r Sys.Date()`"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{An Introduction to eAnalytics}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+eAnalytics is a [Shiny](http://shiny.rstudio.com) web application built on top of [R](https://www.r-project.org) for energy-related data analytics. The app is powered by the excellent [plotly](https://plot.ly/r/), [Leaflet](https://rstudio.github.io/leaflet/), [DT](https://rstudio.github.io/DT/), and [googleVis](https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis_examples.html) packages. To learn more about our project, see this [publication](http://ascelibrary.org/doi/abs/10.1061/9780784413012.143).
+
+# Getting Started
+To install eAnalytics in R:
+
+```c
+install.packages("eAnalytics")
+```
+
+Or to install the latest developmental version:
+
+```c
+devtools::install_github('paulgovan/eAnalytics')
+```
+
+To launch the app:
+
+```c
+eAnalytics()
+```
+
+Or to access the app through a browser, visit [paulgovan.shinyapps.io/eAnalytics](https://paulgovan.shinyapps.io/eAnalytics).
+
+# Data
+eAnalytics is built around the [energyr](https://github.com/paulgovan/energyr) R package of data published by the United States Federal Energy Regulatory Commission [www.ferc.gov](www.ferc.gov). energyr contains several datasets for different industry segments:
+
+* Electric Company Financial Data
+* Natural Gas Company Financial Data
+* Hydropower Plant Data
+* LNG Plant Data
+* Oil Company Financial Data
+* Natural Gas Pipeline Project Data
+* Natural Gas Storage Field Data
+
+# Tutorial
+
+## Dashboard
+Launching the app first brings up the Dashboard tab, which is basically a landing page that gives a brief introduction to the app and includes three value boxes for the current number of projects, companies, and facilities in the database. 
+
+<img src="https://github.com/paulgovan/eAnalytics/blob/master/inst/images/Dashboard.png?raw=true" height="500px" />
+
+## Profile
+The Profile tab contains a number of interactive maps with information about facilities for the selected industry. The figure below shows the Profile tab for the Natural Gas Industry.
+
+Multiple options are currently available for customizing the maps. Choose a preferred size or color variable in the movable well panel, select from different basemaps via the lower-right control, and click on a specific facility to view additional information.
+
+<img src="https://github.com/paulgovan/eAnalytics/blob/master/inst/images/Profile2.png?raw=true" height="500px" />
+
+## Performance
+The Performance tab tracks a number of Key Performance Indicators (KPIs) for the selected industry. The following figure shows the Performance tab for the Natural Gas Industry.
+
+<img src="https://github.com/paulgovan/eAnalytics/blob/master/inst/images/Performance2.png?raw=true" height="500px" />
+
+## Trends
+
+The Trends tab contains multiple interactive time-series charts of financial information for the selected industry. The following figure shows the Performance tab for the Electric industry.
+
+The time-series chart in the Trends tab is linked to the data table shown in the Data tab. Searching, filtering, and sorting the data in the data table will automatically update the time-series chart with the selected data.
+
+<img src="https://github.com/paulgovan/eAnalytics/blob/master/inst/images/Trends2.png?raw=true" height="500px" />
+
+## Data 
+The Data tab contains interactive datatables of information for the selected industry. The data can be searched, filtered, and sorted as required. The selected data can then be copied to the clipboard, downloaded to a csv or pdf file, or sent to a local printer. The figure below shows the Data tab for the Hydropower industry.
+
+<img src="https://github.com/paulgovan/eAnalytics/blob/master/inst/images/Data.png?raw=true" height="500px" />
+
+## Explorer
+The Explorer tab contains a dynamic motion chart for exploring several indicators over time. The following figure shows the Explorer tab for the Natural Gas Industry.
+
+<img src="https://github.com/paulgovan/eAnalytics/blob/master/inst/images/Explorer2.png?raw=true" height="500px" />
+
+# Source Code
+eAnalytics is an [open source](http://opensource.org) project, and the source code and project data is available at [https://github.com/paulgovan/eAnalytics](https://github.com/paulgovan/eAnalytics)
+
+# Issues
+For issues or requests, please use the GitHub issue tracker at [https://github.com/paulgovan/eAnalytics/issues](https://github.com/paulgovan/eAnalytics/issues)
+
+# Contributions
+Ccontributions are welcome by sending a [pull request](https://github.com/paulgovan/eAnalytics/pulls)
+
+# License
+eAnalytics is licensed under the [Apache](http://www.apache.org/licenses/LICENSE-2.0) licence. &copy; Paul Govan (2016)