jbkunst

# setup -------------------------------------------------------------------
library(tidyverse)

data <- read_csv("https://raw.githubusercontent.com/MattLunkes/GoT_Affiliations/master/got_char.csv")
data


data_long <- data %>%
  janitor::clean_names() %>% 
  rename(end_of_s0 = starting_affiliation) %>%

jbkunst

library(tidyverse)
library(rvest)

get_uf <- function(y) {
  
  # y <- 2016
  
  message(y)
  
  seleccionador <- ifelse(y <= 2012, first, last) 

jbkunst

.First <- function(){
  .libPaths("~/R/win-library/")
}

jbkunst

# x <- "https://raw.githubusercontent.com/melvidoni/r4ds/traduccion_melina/factors.Rmd"
# x <- "https://raw.githubusercontent.com/melvidoni/r4ds/traduccion_melina/datetimes.Rmd"

chequear_traduccion <- function(x = "https://raw.githubusercontent.com/melvidoni/r4ds/traduccion_melina/factors.Rmd") {
  
  library(tidyverse)
  library(hunspell)
  library(tidytext)
  
  data <- obtener_data(x)

jbkunst

# packages ----------------------------------------------------------------
rm(list = ls())
library(tidyverse)
theme_set(theme_minimal())


# data --------------------------------------------------------------------
n <- 500
df <- data_frame(
  x1 = rnorm(n) + 1,

jbkunst

rm(list = ls())
library(tidyverse)
library(viridis)
theme_set(theme_minimal())

n <- 1000
s <- seq(1, n)

x <- sqrt(s) + rnorm(n) +  log(s) * rnorm(n)

jbkunst

rm(list = ls())
library(partykit)
library(tidyverse)

iris2 <- iris %>% 
  tbl_df() %>% 
  mutate(Species = as.character(Species),
         Species = ifelse(Species == "setosa", "versicolor", Species),
         Species = as.factor(Species))

jbkunst

Arbol de decisión:
  
  Algoritmo que divide recursivamente grupo de observaciones según valores
  de variables de acuerdo a una variable de interés y una medida de separación.
  El objetivo de usar el árbol de decisión es obtener grupos de observaciones 
  en donde cada segmento tenga distribuciones disimiles de la variable de interés

Random Forest:
  
  Es una colección de árboles de decisión tales que cada árbol es construido

jbkunst

x <- system("ipconfig", intern=TRUE)
x[grep("IPv4", x)]
z <- x[grep("IPv4", x)]
ip <- gsub(".*? ([[:digit:]])", "\\1", z)

runApp(host = ip)

jbkunst

# run via
# source("https://gist.githubusercontent.com/jbkunst/981a6416025d3d7d80303bc20e5269fa/raw/install.packages.R")

install.packages(c(
  # tidyverse
  "tidyverse", "broom",
  # io
  "RODBC", "odbc", "readxl", "writexl", "dbplyr",
  # development
  "devtools", "testthat", "roxygen2", "assertthat",