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library(timeseriesdb) # enthält Demo dataset
library(data.table)
library(tsbox) # time series toolbox von Christoph
# for better overview
tsl <- kof_ts[[20:70]] 
dt <- tsbox::ts_dts(tsl)
dt_wide <- dcast(dt, time ~ id, value.var = "value")
fwrite(dt_wide, file = "triangle.csv")

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rgb2hex <- function(r,g,b) sprintf('#%s',paste(as.hexmode(c(r,g,b)),collapse = ''))

rgb2hex(255,0,0)
# returns '#ff0000'

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# load packages - install from CRAN if you don't have the package:
# install.packages("waffle")
library(waffle)

# all data taken from 
# basketball-reference.com - keep up the great work!
dubs <- c("X3p" = 251,"X2p" = 552 ,"FT" = 333) 
dubs_points_scored <- dubs * c(3,2,1)
names(dubs_points_scored) <- c("by 3s","by 2s","by FTs")

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#!/usr/bin/env bash

# extend resources list and install R
sudo bash -c "echo 'deb http://stat.ethz.ch/CRAN/bin/linux/ubuntu trusty/' >> /etc/apt/sources.list"
sudo apt-get update
sudo apt-get install r-base

# install postgresql
sudo apt-get install postgresql

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dpl_gr <- function(ds,vars){
  ds %>% 
    group_by_(.dots = vars) %>% 
    summarise(n = n()) %>% 
    mutate(freq = n / sum(n))
}

dpl_gr(mtcars,c("am","cyl"))

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• KOF Indicator Dashboard Shiny App
• Data Driven Documents Mike Bostock
• Highcharts Graphic Library
• dygraphs for R
• CRAN Task View (Disciplinary Package Overview
• Shiny Progress Bars
• Shiny CSS loaders (R package for spinners)
• drop R shiny app source Code

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library(MASS)
set.seed(123)
m <- mvrnorm(10000, mu = c(20,2.6),
               Sigma = matrix(c(8,0.85,0.85,.57),
                              ncol = 2),
               empirical = TRUE)

disp <- m[,1]
wt <- m[,2]
am <- rbinom(10000,1,.4)

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computeScores <- function(dframe,
                          maplist,
                          fct = sum,
                          na.rm = T){
  li <- lapply(maplist,function(x){
    out <- dframe[,grep(x,names(dframe),value=T)]
    apply(out,1,fct, na.rm = na.rm)
  })

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# # convenience package... 
# central vs. decentralized production discussion
# not part of this. 

# minimal introduction to R
# different editors and an interpreter
# How-to-R Studio
# # 4 Panes
# # the ctrl+1 ctrl+2 shortcut
# # don't store

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library(openxlsx)
library(rvest)

journals <- read_html("https://www.aeaweb.org/econlit/journal_list.php")

j <- journals %>%
  html_nodes(".journal") %>%
  html_text()

dflist <- lapply(j,function(x){