djnavarro

library(tidyverse)
library(e1071)
library(gganimate)

# parameters for the simulation
ntimes <- 100
nseries <- 20

# construct tibble storing simulation
tbl <- tibble(

DavisVaughan

# SCROLL TO THE GITHUB COMMENT BELOW FOR THE FULL OUTPUT WITH IMAGES
# COPY AND PASTE THIS FOR EASY ACCESS TO REPRODUCIBLE CODE

# ------------------------------------------------------------------------------
library(tidygraph)
library(ggraph)
library(dplyr)
library(igraph)
library(tibble)

hrbrmstr

library(ggplot2)
library(dplyr)

ft <- read.csv("ftpop.csv", stringsAsFactors=FALSE)

arrange(ft, start_year) %>%
  mutate(country=factor(country, levels=c(" ", rev(country), "  "))) -> ft

ft_labs <- data_frame(
  x=c(1900, 1950, 2000, 2050, 1900, 1950, 2000, 2050),

expersso

library(purrr)
library(dplyr)
library(rvest)
library(stringr)
library(geoparser)

w_msg <- function(f) {
  force(f)
  function(...) {
    args <- list(...)

expersso

read_sheet <- function(file, sheet) {
  readxl::read_excel(file, sheet, skip = 6) %>% clean_data()
}

fix_names <- function(df) {
  names(df)[1] <- "location"
  names(df)[-1] <- paste(rep(c(2000, 2014), each = length(names(df)[-1]) / 2), 
                         names(df)[-1], sep = "_")
  df
}

hrbrmstr

library(jsonlite)
library(tigris)
library(ggplot2)
library(purrr)
library(tidyr)
library(dplyr)
library(sp)
library(rgeos)
library(rgdal)
library(maptools)

hrbrmstr

rasmusab

# A Bayesian model that calculates a probability that a couple is fertile 
# and pregnant. Please use this for fun only, not for any serious purpose 
# like *actually* trying to figure out whether you are pregnant.

# Enter your own period onsets here:
period_onset <- as.Date(c("2014-07-02", "2014-08-02", "2014-08-29", "2014-09-25", 
                          "2014-10-24", "2014-11-20", "2014-12-22", "2015-01-19"))
# If you have no dates you can just set days_between_periods to c() instead like:
# days_between_periods <- c()
days_between_periods <- as.numeric(diff(period_onset))

johnburnmurdoch

library(SmarterPoland)
library(riverplot)
library(RColorBrewer)
library(graphics)
library(reshape2)
library(plyr)
library(stringr)
library(countrycode)

# DOWNLOAD THE DATA

rich-iannone

# Installation
#install.packages("devtools")
devtools::install_github("rich-iannone/DiagrammeR")

library(DiagrammeR)

# Create and render an empty graph
empty_graph <- create_graph()
render_graph(empty_graph, output = "visNetwork")