Standby.Rmd

Unzip
Download zip files

Connection to db
DBI

Paste collapse

Str evaluation

File string


Web scraping
Rest
Divs

Dates and times
As.date
Sys.date

Lubridate
Stringr
Rebus


Grep
Grepl
Gsub
Nchar


Loading data objects
Load data

Fileinfo

Paste
Regex



Shapefile

Joins

----------------------------------------------

https://www.sqlitetutorial.net/sqlite-sample-database/

https://towardsdatascience.com/if-marie-kondo-did-sql-be86374b7cd8




Kevin O'Brien <kobriendublin@gmail.com>
Fri, 16 Jun, 14:28
to me

magicK Rpackage

The magick package: Advanced Image-Processing in R • magick (ropensci.org)
Colour palettes



Everything is an object in R. What exactly is an object in R? As in real life, it can be difficult to give a definition, but easier to give examples. 



---------------------------------------------------


## Managing Files

An important skill set is our is to be able to efficiently manage files and directories in the System.

There are several base, our packages, that allow files to be created, or checks to see if they exist.

Likewise with directories.

Additional functionality is provided by the {ff} R package.

Files can be transferred from one location to another.






------------------------------

radio_button_choices = list(                          
  "YTGen Forecasts"=1, 
  "Yield Insights" = 2,
  "PSM2i Insights" = 3,
  "Products"=4,
  "Maps" = 5, 
  "Time Series" = 6,
  "Additional Information" = 7)



  observeEvent(input$controller, {
    #req(credentials()$user_auth)
    updateTabsetPanel(session, "hidden_tabs", selected =  paste0("Panel ", input$controller))
  })
  
  Region = reactive({input$Region})
  
  #  output$Deadwood_Volume <- renderUI({Deadwood_Volume})
  #  output$Environmental_Stats_Intro <- renderUI({Environmental_Stats_Intro})
  #   output$Env_Matrix_ft <- renderUI({
  #    ThisRegion = Region()
  #    ThisMatrix = paste0("Matrix_",ThisRegion,".html")
  #    
  #    })
  
------------------------------
#### Task Scheduler

* https://cran.r-project.org/web/packages/taskscheduleR/vignettes/taskscheduleR.html

------------------------------
### Scope

This talk is about the R programming language and Association or packages and features.

A workflow for developing shiny apps and flex.


-----------------------------------

### Audience

I go to assume that everyone has a certain reasonable knowledge of Open Source tools such as leaflet.
 * However I'll talk about them briefly and introduce them briefly needless to say that most

Open source, GIS tools, have some sort of interface or implementation with our so,

They are, you probably know them already are. That's worth. Let's talk in its own right?

-----------------------------------

### R packages

ggplot and plotlt

Leaflet.js

-----------------------------------

### Dashboards

So, the two main tools, I will be using for dashboards are Flex dashboard. Which a very simple system.

And shiny dashboards? 

Supposition: Medium level of complexity.
Can not divert a lot of time and/or resource to developing it

---------------------------

#### Complexity Requirements

I just got to make a few observations about how to get the most out of them. Also, I've been taking the point of view that

Coming at it, from the perspective of somebody who needs a reason to be integrated and Technical dashboard boss, who not to the extent that they would need to have a very elaborate implementation. That requires a specialist, shiny developer. So the middle ground but nothing too simple. That essentially, a novice should be able to pick up very easily.



----------------------------------

#### Construction

The core pieces of information are straightforward. Leaflet provides the map.

And I am able to source of locations of

Interesting, venues myself as a hobby.


--------------------------------

#### HTML and RMarkdown Modules 

* Preformatted Text as a function
* Equivalents of Standard HTML tags
* There is one exception to this rule is that you can using WithHTML. 

------------------------------

radio_button_choices = list(                          
  "YTGen Forecasts"=1, 
  "Yield Insights" = 2,
  "PSM2i Insights" = 3,
  "Products"=4,
  "Maps" = 5, 
  "Time Series" = 6,
  "Additional Information" = 7)



  observeEvent(input$controller, {
    #req(credentials()$user_auth)
    updateTabsetPanel(session, "hidden_tabs", selected =  paste0("Panel ", input$controller))
  })
  
  Region = reactive({input$Region})
  
  #  output$Deadwood_Volume <- renderUI({Deadwood_Volume})
  #  output$Environmental_Stats_Intro <- renderUI({Environmental_Stats_Intro})
  #   output$Env_Matrix_ft <- renderUI({
  #    ThisRegion = Region()
  #    ThisMatrix = paste0("Matrix_",ThisRegion,".html")
  #    
  #    })
  

------------------------------

Tidyverse vs Base R

Base R making a comeback

Expert Beginner Problem

Maturity

* https://news.ycombinator.com/item?id=19467367#:~:text=The%20problem%20with%20the%20expert,to%20fall%20into%20the%20trap.

------------------------------
Shiny Conference 
 - 15th March to 17th March - Online
 - Run by Appsilon
 - https://shinyconf.appsilon.com/
 - Future Forests - https://connect.appsilon.com/future-forests/
------------------------------

Coursera Specialization Courses
 - Tidyverse
 - Shiny and Dashboards

Kevin O'Brien <kobriendublin@gmail.com>
Wed, 6 Sept, 21:24
to me

Version 3


-----------------------------------

### R packages

ggplot and plotlt

Leaflet.js


---------------------------

#### Complexity Requirements

I just got to make a few observations about how to get the most out of them. Also, I've been taking the point of view that

Coming at it, from the perspective of somebody who needs a reason to be integrated and Technical dashboard boss, who not to the extent that they would need to have a very elaborate implementation. That requires a specialist, shiny developer. So the middle ground but nothing too simple. That essentially, a novice should be able to pick up very easily.




------------------------------

radio_button_choices = list(                          
  "YTGen Forecasts"=1, 
  "Yield Insights" = 2,
  "PSM2i Insights" = 3,
  "Products"=4,
  "Maps" = 5, 
  "Time Series" = 6,
  "Additional Information" = 7)



  observeEvent(input$controller, {
    #req(credentials()$user_auth)
    updateTabsetPanel(session, "hidden_tabs", selected =  paste0("Panel ", input$controller))
  })
  
  Region = reactive({input$Region})
  
  #  output$Deadwood_Volume <- renderUI({Deadwood_Volume})
  #  output$Environmental_Stats_Intro <- renderUI({Environmental_Stats_Intro})
  #   output$Env_Matrix_ft <- renderUI({
  #    ThisRegion = Region()
  #    ThisMatrix = paste0("Matrix_",ThisRegion,".html")
  #    
  #    })
  

------------------------------

Tidyverse vs Base R

Base R making a comeback

Expert Beginner Problem

Maturity

* https://news.ycombinator.com/item?id=19467367#:~:text=The%20problem%20with%20the%20expert,to%20fall%20into%20the%20trap.