wch

max_plots <- 5

ui <- fluidPage(

  headerPanel("Dynamic number of plots"),

  sidebarPanel(
    sliderInput("n", "Number of plots", value=1, min=1, max=5)
  ),

MarkEdmondson1234

library(shiny)

#' Safe subset
#'
#' @param df Dataframe
#' @param column One name of column to subset within
#' @param subset Vector of entries in column to subset to
#'
#' If column not in df, returns back the df
safeSubset <- function(df, column, subset){

jcheng5

library(shiny)

columnFilterUI <- function(id) {
  ns <- NS(id)
  uiOutput(ns("filter_container"))
}

columnFilter <- function(input, output, session, df, col_num, choice_filter) {
  # This renders a selectInput and only re-renders when the selected data
  # frame changes. (i.e. it doesn't re-render when filters change state.)

volpefoxx

import requests
import json
import re
from more_itertools import unique_everseen

with open("urls.json", "r", encoding="utf-8") as fp:
    urls = json.load(fp)

# lots of regex to extract video ID from different types of YouTube links
def get_id(url):

calligross

library(shiny)
library(shinyjs)

if (!dir.exists('www/')) {
  dir.create('www')
}

download.file(
  url = 'https://cdn.jsdelivr.net/npm/js-cookie@2/src/js.cookie.min.js',
  destfile = 'www/js.cookie.js'

jcheng5

library(shiny)

# WARNING: This sketch does not make proper use of the "state" parameter.
# Doing so usually involves using cookies, which can be done with the
# Rook package but I have not done that here. If you choose to use this
# approach in production, please check the state parameter properly!

APP_URL <- if (interactive()) {
  # This might be useful for local development. If not, just hardcode APP_URL
  # to the deployed URL that you'll provide a few lines below.

karawoo

## Start with the code and data here: https://github.com/fivethirtyeight/data/blob/master/police-deaths/plot.R

## Then:
## Calculate total deaths by year
dat <- data_for_plot %>%
  group_by(year) %>%
  mutate(total = sum(count))

## Colors I chose
mycolors <- c("#00bf7b", "#59004d", "#ffcb89", "#a76e61", "#ac270d", "#7890ff",

zross

• Eurostat, World Bank and others: https://ikashnitsky.github.io/2017/data-acquisition-two/
• Star Wars data: in dplyr, http://dplyr.tidyverse.org/reference/starwars.html
• Baby names data: babynames package, https://cran.r-project.org/web/packages/babynames/index.html
• Movies data: https://cran.r-project.org/web/packages/ggplot2movies/index.html ggplot2movies package
• Game of Thrones screen time: https://github.com/Preetish/GoT_screen_time
• Open Bike Data: https://github.com/ropensci/bikedata
• Tons of data through 538: https://cran.r-project.org/web/packages/fivethirtyeight/vignettes/fivethirtyeight.html
• Public health data England: fingertipsR, https://cran.r-project.org/web/packages/fingertipsR/
• Financial data via Quandl: https://www.quandl.com/tools/r
• Cyclones: https://github.com/ropensci/rrricanesdat

timelyportfolio

Let's say you have streaming data, and you would like to update a DT::datatable in Shiny without completely re-rendering the table. Here is some code to illustrate how this might be accomplished. Hope it helps.

library(DT)
library(shiny)

ui <- tagList(
  tags$script(HTML(
"
Shiny.addCustomMessageHandler(

thomasp85

library(gganimate) # thomasp85/gganimate
library(cartogram)
library(geogrid) # Need github version jbaileyh/geogrid
library(rnaturalearth)
library(sf)
library(scico)

us <- ne_states('united states of america', returnclass = 'sf')
us <- us[!us$woe_name %in% c('Alaska', 'Hawaii'), ]
us <- st_transform(us, '+proj=eqdc +lat_0=39 +lon_0=-96 +lat_1=33 +lat_2=45 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs')