daattali

[{"CountryList": ["Austria", "Germany", "Italy", "Spain", "United Kingdom"], "Sector3": "Commercial Leases"}, {"CountryList": ["Belgium", "France", "Germany", "Ireland", "Italy", "Netherlands", "Portugal", "Spain", "United Kingdom"], "Sector3": "Residential Mortgage"}, {"CountryList": ["Belgium", "France", "Ireland", "Spain", "United Kingdom"], "Sector3": "Credit Card"}, {"CountryList": ["Belgium", "Germany", "Italy", "Portugal", "Spain"], "Sector3": "SME CLO"}, {"CountryList": ["France", "Germany", "Netherlands"], "Sector3": "Auto Leases"}, {"CountryList": ["France", "Germany", "Italy", "Netherlands", "Norway", "Portugal", "Spain", "United Kingdom"], "Sector3": "Auto Loans"}, {"CountryList": ["France", "Germany", "Italy", "Netherlands", "Portugal", "Spain", "Sweden"], "Sector3": "Consumer Loans"}, {"CountryList": ["France", "Portugal", "United Kingdom"], "Sector3": "Mixed Auto Loans and Leases"}, {"CountryList": ["Germany", "Ireland", "Italy", "Spain"], "Sector3": "Consumer and Commercial Leases"}, {"Country

daattali

# Get a person's name, location, summary, # of connections, and skills & endorsements from LinkedIn

# URL of the LinkedIn page 
user_url <- "https://www.linkedin.com/in/daattali"

# since the information isn't available without being logged in, the web
# scraper needs to log in. Provide your LinkedIn user/pw here (this isn't stored
# anywhere as you can see, it's just used to log in during the scrape session)
username <- "yourusername"
password <- "yourpassword"

daattali

library(shiny)

ui <- fluidPage(
  shinyjs::useShinyjs(),
  
  # You have to include this one-liner CSS
  tags$style(".fullwidth { width: 100% !important; }"),
  
  # You need to wrap the sidebarLayout() by a div() and give it an ID
  div(id = "SOMEID",

daattali

library(dplyr)
rawDataUrl <- "http://pub.data.gov.bc.ca/datasets/176284/BC_Liquor_Store_Product_Price_List.csv"
bcl <- read.csv(rawDataUrl, stringsAsFactors = FALSE)
products <- c("BEER", "REFRESHMENT BEVERAGE", "SPIRITS", "WINE")
bcl <- dplyr::filter(bcl, PRODUCT_CLASS_NAME %in% products) %>%
  dplyr::select(-PRODUCT_TYPE_NAME, -PRODUCT_SKU_NO, -PRODUCT_BASE_UPC_NO,
                -PRODUCT_LITRES_PER_CONTAINER, -PRD_CONTAINER_PER_SELL_UNIT,
                -PRODUCT_SUB_CLASS_NAME) %>%
  rename(Type = PRODUCT_CLASS_NAME,
         Subtype = PRODUCT_MINOR_CLASS_NAME,

daattali

library(shiny)

# Define the fields we want to save from the form
fields <- c("name", "used_shiny", "r_num_years")

# Save a response
# ---- This is one of the two functions we will change for every storage type ----
saveData <- function(data) {
  data <- as.data.frame(t(data))
  if (exists("responses")) {

daattali

# I'm trying to let the user select points and paint them in a certain colour, and if the user clicks on a point then paint that point a different colour.
# It looks like the pointNumber and curveNumber data that plotly returns are different for the same points. I'm not sure how curveNumber works, but to me it doesn't make sense yet :)
# Any help is appreciated!

library(plotly)
library(shiny)

ui <- fluidPage(
  plotlyOutput("plot")
)

daattali

library(shiny)
library(datasets)

Logged = FALSE;
PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad")
# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {
  source("www/Login.R",  local = TRUE)
  
  observe({

daattali

#' Suppress all output from an expression. Works cross-platform.
#' @param expr Expression to run.
#' @param all If \code{TRUE} then suppress warnings and messages as well;
#' otherwise, only suppress printed output (such as from \code{print} or
#' \code{cat}).
#' @keywords internal
#' @export
quiet <- function(expr, all = TRUE) {
  if (Sys.info()['sysname'] == "Windows") {
    file <- "NUL"

daattali

library(shiny)
library(ggplot2)

makePlot <- function(xvar, yvar) {
  ggplot(iris, aes_string(xvar, yvar)) + geom_point()
}

ui <- fluidPage(
  selectInput("xvar", "X variable", choices = names(iris), selected = names(iris)[1]),
  selectInput("yvar", "Y variable", choices = names(iris), selected = names(iris)[2]),

daattali

# This script uploads all the FAST files to the taxonomer server (only one file can be uploaded at a time)
# Assumes that you have RSelenium package installed and that you've got a simple selenium example to work

if (FALSE) {
  fastq_files <- c(
    list.files(# WHERE ARE THE FILES?, pattern = "fastq.gz$", full.names = TRUE)
  )
  login_password <- "" # what is my password???
  
  library(RSelenium)