R

QuartzMap supports creating of a number of R HTML applications:

  1. R Leaflet: https://github.com/rstudio/leaflet/

  2. Plotly: https://plotly.com/r/

  3. Standard Plots

R Publishing

There are three options for publising your R code.

Option 1: FTP.

FTP Uploads are R files you have uploaded directly via FTP.

It can also maps you uploaded via any FTP client.

_images/Map-2.png

Option 2: Archive (Upload)

Archive is a zipped archive file you can upload.

_images/Map-3.png

Option 3: Paste

Paste your R Leaflet code into the code box.

_images/R-Paste.png

R Leaflet

To create an R Leaflet Map, click on “Add New” button.

FTP, Upload, or Paste your code.

Give your R code a Name and Description.

Example

The two main components are the libraries and saveWidget function

#libraries
library(leaflet)
library(leaflet.extras)
require(sf)
library(htmlwidgets)

# Your R Code Here

#saveWidget
saveWidget(m, file = "index.html")

An example Choropleth map is included in the installation.

library(leaflet)
library(leaflet.extras)
require(sf)
library(htmlwidgets)


# From https://leafletjs.com/examples/choropleth/us-states.js
     states <- sf::read_sf("https://rstudio.github.io/leaflet/json/us-states.geojson")

     bins <- c(0, 10, 20, 50, 100, 200, 500, 1000, Inf)
     pal <- colorBin("YlOrRd", domain = states$density, bins = bins)

     labels <- sprintf(
       "<strong>%s</strong><br/>%g people / mi<sup>2</sup>",
       states$name, states$density
     ) %>% lapply(htmltools::HTML)

m <- leaflet(states) %>%
     setView(-96, 37.8, 4) %>%
     addPolygons(
     fillColor = ~pal(density),
     weight = 2,
     opacity = 1,
     color = "white",
     dashArray = "3",
     fillOpacity = 0.7,
     highlightOptions = highlightOptions(
     weight = 5,
     color = "#666",
     dashArray = "",
     fillOpacity = 0.7,
     bringToFront = TRUE),
     label = labels,
     labelOptions = labelOptions(
     style = list("font-weight" = "normal", padding = "3px 8px"),
     textsize = "15px",
     direction = "auto")) %>%
addLegend(pal = pal, values = ~density, opacity = 0.7, title = NULL,
     position = "bottomright") %>%
addTiles(group="OpenStreetMap") %>%
addProviderTiles(providers$Esri.WorldImagery, group = "Esri World Imagery") %>%
addLayersControl(baseGroups=c("OpenStreetMap", "Esri World Imagery"), options=layersControlOptions(collapsed=FALSE)) %>%
addMeasurePathToolbar(options = measurePathOptions(imperial = FALSE, showDistances = TRUE)) %>%
addDrawToolbar(
     targetGroup = "draws",
     editOptions = editToolbarOptions(
     selectedPathOptions = selectedPathOptions()))

saveWidget(m, file = "index.html")

The output should look as below:

_images/R-Choropleth.png

R Plotly

To create an R Plotly Animated App, click on “Add New” button.

FTP, Upload, or Paste your code.

Give your R code a Name and Description.

Example

The example is animated Plotyl map with Play button.

The three main components in this example are the plotly, dplyr, and htmlwidgets function.

# Main libraries for Plotly
  library(dplyr)
  library(plotly)
  library(htmlwidgets)

# Your R Code Here

#saveWidget
htmlwidgets::saveWidget(as_widget(p), file="index.html")

An example of a Plotly app is included in the installation. Here, we add the RPostgreSQL library to connect to PostgreSQL.

#load library
library(dplyr)
library(plotly)
library(htmlwidgets)

#load data
df <- read.csv("graph.csv")

#create map
p <- plot_geo(df, locationmode = 'world') %>%
        add_trace( z = ~df$new_cases_per_million, locations = df$code, frame=~df$start_of_week, color = ~df$new_cases_per_million)

#export as html file
htmlwidgets::saveWidget(p, file = "index.html")

The output should look at below:

_images/R-Animated.png

R Plotly Dynamic Data (PostgreSQL)

To create an R Plotyl App with Dynamic Data, click on “Add New” button.

FTP, Upload, or Paste your code.

Give your R code a Name and Description.

Example

The main components in this example are the plotly, ggplot2, RPostgreSQL, and htmlwidgets function.

# Main libraries for Plotly
   library(plotly)
   library(ggplot2)
   library(RPostgreSQL)
   library(htmlwidgets)

# Your R Code Here

#saveWidget
htmlwidgets::saveWidget(as_widget(p), file="index.html")

The example is chart with dynamic PostgreSQL connection is contained in the Sample Apps (Simple Bee Harvest)

Here, we add the RPostgreSQL library to connect to PostgreSQL.

library(plotly)
library(ggplot2)
library(RPostgreSQL)
library(htmlwidgets)

conn <- RPostgreSQL::dbConnect("PostgreSQL", host = "localhost", dbname = "beedatabase", user = "admin1", password = "ORUVDrYBCQ")

query_res <- dbGetQuery(conn, 'select area_id,bee_species,sum(average_harvest) from public.apiary GROUP BY (area_id,bee_species) ORDER BY(area_id)');
area_harvest <- as.data.frame(query_res);

p <- plot_ly(area_harvest, x=~area_id, y=~sum, type="bar",
          text = ~bee_species, textposition = 'auto') %>%
     layout(title = "Accumulated Average Harvest per Area for Apis Mellifera Carnica",
   xaxis = list(title = "Area ID"), yaxis = list(title = "Average Harvest"))


htmlwidgets::saveWidget(as_widget(p), file="index.html")

The output should look at below:

_images/rplotly-postgresql.png

R Standard Plot (PNG)

To create an R Standard Plot (PNG) Map, click on “Add New” button.

FTP, Upload, or Paste your code.

Give your R code a Name and Description.

Example

The three main components are the R3port and html_plot function.

# Main libraries for Plotly
library(R3port)

# Your R Code Here

#output
html_plot(pl(),      out="index.html")

An example of a Standard Plot (PNG) is included in the installation.

library(R3port)

set.seed(1919)                                 # Create example data
x1 <- rnorm(1000)
y1 <- x1 + rnorm(1000)

group <- rbinom(1000, 1, 0.3) + 1              # Create group variable

pl <- function() {
        plot(x1, y1,                                   # Create plot with groups
      main = "This is my Plot",
      xlab = "X-Values",
      ylab = "Y-Values",
      col = group,
      pch = group)

   legend("topleft",                              # Add legend to plot
      legend = c("Group 1", "Group 2"),
      col = 1:2,
      pch = 1:2)
   }

html_plot(pl(),      out="index.html")

R Report (RMD)

To create an R Report App, click on “Add New” button.

FTP, Upload, or Paste your code.

Give your R code a Name and Description.

Example

The Demo Data contains a full R Report.

It is the “My Super Fancy Report” created by David Keyes

https://rfortherestofus.github.io/fundamentals/sample-report.html

---
title: "My Super Fancy Report"
author: "David Keyes"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```


# Introduction

This report is the best report ever. Pretty much the **bees' knees**. Can't say that I've *ever* seen a better report.

## Reasons Why This Report is the Best

- It's amazing
- It's quite amazing
- It's seriously amazing

## R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.

When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

```{r cars, include = FALSE}
summary(cars)
```

## Including Plots

You can also embed plots, for example:

```{r pressure, echo=FALSE}
plot(pressure)
```


Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.


```{r warning = FALSE, message = FALSE}
library(skimr)

skim(cars)
```

The output should look at below:

_images/r-report.png

R App Options

Name

Give your R app a name. The name will appear as the map title on the dashboard.

_images/Name-Desc.png

Description

The Description is the text that will appear at the bottom of the map link

_images/Name.png

Data Update (Cache)

For dynamic R apps that connect to a databases, you can set the update frequency

_images/Update.png

If you wish to set a custom interval, select custom:

_images/Update-2.png

When Updates are selected, this is the interval at which your app will be recompiled against the database.

If you have enabled Updates, but wish to Update immediately, you can do so by clicking the Clear Cache icon on the Map page:

_images/clear-cache.png

Thumbnail Image:

Upload a thumbnail image for your map to be displayed on the home page.

_images/Thumbnail.png

Info Box.

The InfoBox is a modal information box you can display to map users.

_images/Info-Box.png

Security

Maps can be Private or Public.

The Security section is where you assign permissions to your map.

Security is Group based, so any users belonging to the Group will be able to view the map.

_images/users-3.jpg

  1. Private

Private apps can be viewed by the user logging into your map portal or via Secure Share link (for temporary access)

For example, since we gave access to the Group containing user Jane Doe, when she logs in she will see only the two maps she has permissions to

_images/users-2.jpg

  1. Public

You can also tick the “Public” box to make your app public.

_images/public-users.jpg

If your map is “Public”, you can use the map url to display the map.

By default, the app is full screen. You can also use an iframe.