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*******
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
.. contents:: Table of Contents
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.
.. image:: Map-2.png
Option 2: Archive (Upload)
------------
Archive is a zipped archive file you can upload.
.. image:: Map-3.png
Option 3: Paste
-----------------
Paste your R Leaflet code into the code box.
.. image:: 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
.. code-block:: R
#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.
.. code-block:: R
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:
.. image:: 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.
.. code-block:: R
# 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.
.. code-block:: R
#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:
.. image:: 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.
.. code-block:: R
# 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.
.. code-block:: R
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:
.. image:: 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.
.. code-block:: R
# 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.
.. code-block:: R
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
.. code-block:: R
---
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:
.. image:: r-report.png
R App Options
===================================
Name
--------------
Give your R app a name. The name will appear as the map title on the dashboard.
.. image:: Name-Desc.png
Description
--------------
The Description is the text that will appear at the bottom of the map link
.. image:: Name.png
Data Update (Cache)
--------------
For dynamic R apps that connect to a databases, you can set the update frequency
.. image:: Update.png
If you wish to set a custom interval, select custom:
.. image:: 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:
.. image:: clear-cache.png
Thumbnail Image:
--------------
Upload a thumbnail image for your map to be displayed on the home page.
.. image:: Thumbnail.png
Info Box.
--------------
The InfoBox is a modal information box you can display to map users.
.. image:: 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.
.. image:: 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
.. image:: users-2.jpg
2. Public
You can also tick the “Public” box to make your app public.
.. image:: 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.