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require(ggplot2) 

# prepare south park data -------------------------------------------------
d2 <- data.frame(member=c(rep("Eric",5),  
                          rep("Kyle",5),  
                          rep("Stan",5),  
                          rep("Kenny",5)),  
                 shade=c("EricPants","EricShirt","Skin","EricHat","EricPomPom",  
                         "KylePants","KyleShirt","Skin","KyleHatBottom","KyleHatTop",  
                         "StanPants","StanShirt","Skin","StanBottom","StanHatTop", 

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require(dplyr)
require(rvest)

options(stringsAsFactors = FALSE)

url_base <- "http://securities.stanford.edu/list-mode.html?page="
tbl.clactions <- data.frame(
  "Filing.Name" = character(0),
  "Filing.Date" = character(0),
  "District.Court" = character(0),

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# create dummy data -------------------------------------------------------
set.seed(1)
d <- data.frame(col1 = sample(letters[1:3], 10, replace=T), 
                col2 = sample(letters[24:26], 10, replace=T),
                col3 = runif(10) * 10, 
                stringsAsFactors = FALSE)

d$col1 <- as.factor(d$col1)
d$col4 = d$col3 + runif(10)

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# Martingale Betting System

# initialize parameters ---------------------------------------------------
init_start <- 12800
init_goal <- init_start + 1000
init_bet <- 100    # initial bet value
prob_win <- 0.47   # probability of win
n <- 500000        # simulation count

# run simulation ----------------------------------------------------------

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# http://www.bnosac.be/index.php/blog/57-new-rstudio-add-in-to-schedule-r-scripts
install.packages('knitr')
install.packages('data.table')
install.packages('shiny')
install.packages('miniUI')
install.packages("taskscheduleR", repos="http://www.datatailor.be/rcube", type="source")

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library(tidyverse)
library(ggrepel)
library(scales)
results <- read_csv("results.csv")

# add GDP rank, winning candidate, chart labels
results <- results %>% 
  arrange(desc(GDP)) %>%
  mutate(GDPRank = 1:51) %>%
  mutate(Win = ifelse(ClintonNum>TrumpNum, "Clinton", "Trump")) %>%

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prop_model <- function (data = c(), prior_prop = c(1, 1), n_draws = 10000, show_plot = TRUE) {
  library(tidyverse)
  library(purrr)
  library(ggjoy)
  data <- as.logical(data)
  proportion_success <- c(0, seq(0, 1, length.out = 100), 1)
  data_indices <- round(seq(0, length(data), length.out = min(length(data) + 1, 20)))
  post_curves <- map_dfr(data_indices, function(i) {
    value <- ifelse(i == 0, "Prior", ifelse(data[i], "Success", "Failure"))
    label <- paste0("n=", i)

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import os
from selenium import webdriver
from selenium.webdriver.common.keys import Keys

import pandas as pd
import numpy as np
import time
from itertools import groupby

def scroll(driver, timeout):

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'Add Microsoft Word XX.0 Object Library in Tools >> References
Public Sub FormatSelectedText()
    Dim objItem As Object
    Dim objInsp As Outlook.Inspector

    Dim objWord As Word.Application
    Dim objDoc As Word.Document
    Dim objSel As Word.Selection
    On Error Resume Next