From 0c073e3ccb598ee3152bf3ec5b1e560f1dca4454 Mon Sep 17 00:00:00 2001
From: AcuGIS <acugis@noreply.localhost>
Date: Sun, 1 Sep 2024 15:01:20 +0000
Subject: [PATCH] Update docs/source/r.rst

---
 docs/source/r.rst | 134 ++++++++++++++++++++++++++++++++++++----------
 1 file changed, 105 insertions(+), 29 deletions(-)

diff --git a/docs/source/r.rst b/docs/source/r.rst
index 62f5eb6..23456e9 100644
--- a/docs/source/r.rst
+++ b/docs/source/r.rst
@@ -143,7 +143,7 @@ The output should look as below:
 R Plotly
 ===================================
 
-To create an R Leaflet Map, click on "Add New" button.
+To create an R Plotly App, click on "Add New" button.
 
    .. image:: images/Add-Map.png
 
@@ -156,14 +156,18 @@ Give your R code a Name and Description.
 Example
 --------------
 
-The three main components are the plotly, ggplot2, and htmlwidgets function.
+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(plotly)
-   library(ggplot2)
-   library(htmlwidgets)
+     library(dplyr)
+     library(plotly)
+     library(htmlwidgets)
 
    # Your R Code Here
 
@@ -176,36 +180,108 @@ An example of a Plotly app is included in the installation.  Here, we add the RP
 
 .. code-block:: R
 
-   library(plotly)
-   library(ggplot2)
-   library(RPostgreSQL)
-   library(htmlwidgets)
+      #load library
+      library(dplyr)
+      library(plotly)
+      library(htmlwidgets)
 
-   conn <- RPostgreSQL::dbConnect("PostgreSQL", host = "localhost", dbname = "r_examples", user = "admin1", password = "4eA7hDlgYF")
+      #load data
+      df <- read.csv("graph.csv")
 
-   query_res <- dbGetQuery(conn, 'SELECT * FROM "sensor_readings";');
-   sensor_readings <- as.data.frame(query_res);
-   # sensor_readings$timestamp <- as.Date(sensor_readings$timestamp)
+      #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)
 
-   p <- plot_ly(sensor_readings, x=~timestamp, y=~humidity, text=~paste("Sensor: ", sensor_name), mode="markers", color=~humidity, size=~humidity) %>%
-	   	layout(
-		   		plot_bgcolor='#e5ecf6',
-			   	xaxis = list(  matches='x',
-				   							 zerolinecolor = '#ffff',
-					   						 zerolinewidth = 2,
-						   					 gridcolor = 'ffff',
-							   				 range = list(	min(sensor_readings$timestamp),
-								       		 max(sensor_readings$timestamp))
-																		),
-				yaxis = list(
-					zerolinecolor = '#ffff',
-					zerolinewidth = 2,
-					gridcolor = 'ffff')
-	   )
-	
+      #export as html file
+      htmlwidgets::saveWidget(p, file = "index.html")
+
+
+
+The output should look at below:
+
+
+   .. image:: images/R-Animated.png
+
+
+
+
+R Plotly Dynamic Data
+===================================
+
+To create an R Plotyl App with Dynamic Data, click on "Add New" button.
+
+   .. image:: images/Add-Map.png
+
+
+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 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")
 
 
+An example of a Plotly app is included in the installation.  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 = "$DB_NAME", user = "$DB_USER", password = "$DB_PASS")
+
+      query_res <- dbGetQuery(conn, 'SELECT * FROM "sensor_readings";');
+      sensor_readings <- as.data.frame(query_res);
+      # sensor_readings$timestamp <- as.Date(sensor_readings$timestamp)
+
+      p <- plot_ly(sensor_readings, x=~timestamp, y=~humidity, text=~paste("Sensor: ", sensor_name), mode="markers", color=~humidity, size=~humidity) %>%
+		      layout(
+				      plot_bgcolor='#e5ecf6',
+				      xaxis = list(  matches='x',
+											 zerolinecolor = '#ffff',
+											 zerolinewidth = 2,
+											 gridcolor = 'ffff',
+											 range = list(	min(sensor_readings$timestamp),
+											 								max(sensor_readings$timestamp))
+																		),
+				      yaxis = list(
+					   zerolinecolor = '#ffff',
+					   zerolinewidth = 2,
+					   gridcolor = 'ffff')
+	   )
+	
+      htmlwidgets::saveWidget(as_widget(p), file="index.html")
+
+
+
+The output should look at below:
+
+
+   .. image:: images/R-Sensor.png
+
 
 R Standard Plot (PNG)
 ===================================