sillasgonzaga

#1 Baixar série historica do dolar de 2 anos
library(quantmod)
library(xlsx)
library(plyr)
library(dplyr)
library(corrplot)

sillasgonzaga

pi_accuracy <- function(fc, yobs){
   # source: http://ellisp.github.io/blog/2016/01/30/hybrid-forecasts
   # checks the success of prediction intervals of an object of class 
   # forecast with actual values
   if(length(yobs) != length(fc$mean)){
      stop("yobs needs to be the same length as the forecast period.")
   }
   n <- length(yobs)
   yobsm <- cbind(yobs, yobs)
   In <- (yobsm > fc$lower & yobsm < fc$upper) 

sillasgonzaga

# source: http://stackoverflow.com/a/21030800/4577128

clipboard <- function(x, sep="\t", row.names=FALSE, col.names=TRUE){
     con <- pipe("xclip -selection clipboard -i", open="w")
     write.table(x, con, sep=sep, row.names=row.names, col.names=col.names)
     close(con)
}

sillasgonzaga

# projeto analise de sentimento
library(tidyr)
library(dplyr)
library(magrittr)
library(stringr)
library(lubridate)
library(ggplot2)
library(tm)
library(SnowballC)
library(wordcloud)

sillasgonzaga

library(stringr)
library(magrittr)
library(lubridate)
library(glue)
library(dplyr)
library(readr)

# exemplo:

extrair_ans_UF <- function(uf, limpar_pasta_temporaria = TRUE) {

sillasgonzaga

# source: https://gist.github.com/corynissen/5389426

getLongURL.curl <- function(shorturl){
  # uses curl statement to get expanded url from t.co links (or any link)
  # loop through until there's no location attribute... that's the long link.
  newurl <- shorturl
  url <- ""
  while(url != newurl){
    data <- system(paste0("curl -I ", newurl), intern=T)
    if(sum(grepl("location: ", tolower(data))) == 0){

sillasgonzaga

library(tidyverse)
library(purrr)
library(forecast)
library(lubridate)

vetor_uf <- c("RJ", "SP", "MG", "ES")

vetor_data <- seq.Date(as.Date("2010-01-01"), by = "month",
                       length.out = 60)

sillasgonzaga

meu_tema <- function(base.size = 9, legend.text.size = 9, axis.text.size = 10, axis.title.size = 11) {

# exemplo da função lm
#ggplot(agua_agregado, aes(x = dif_pressao, y = vazao_massica_media)) +
#  geom_point() + geom_smooth(method = "lm") +

sillasgonzaga

#Code for "A Statistical Curiosity Voyage Through the Emotion of Stranger Things"
#Article and code written by Jordan Dworkin (https://medium.com/@jordandworkin/)


###############################################################################
####### Pull script data (would need to be edited based on data source) #######
###############################################################################

library(rvest)
library(tibble)

sillasgonzaga

grafico_tfidf <- function(data, n_grams = 1, remover_nomes_proprios,
                          agregar_por_noticia, remover_stop_words = TRUE){
  
  data <- data %>% 
    unnest_tokens(palavra, corpo_noticia, token = "ngrams", n = n_grams, to_lower = FALSE)
  
  if (agregar_por_noticia){
    # remover as duplicatas dentre de uma mesma noticia
    data %<>% distinct(url, palavra, .keep_all = TRUE)
  }