Daniel P. Egan bestdan

I hereby claim:

To claim this, I am signing this object:

	#!/usr/bin/env sh


	# # These functions make it easy to look at the output of a dart
	# # test with large non-matching objects.
	#
	# # To use:
	# # One and done:
	# auditDartTest test/example_test.dart 'this test fails'
	#

	#' @title S&P 500 heatmap
	#' @author Daniel Egan
	#' @description Creates real and nominal triangle heatmaps based on the S&P 500.
	#' @details Last update 2012-06-01
	### ----

	library(quantmod)
	library(RColorBrewer)

	#Some useful matrix functions

	#' @title Log-means versus Medians
	#' @author Daniel Egan
	#' @description When data has a power law or extremely skewed distribution,
	#' using a log-mean usually results in more stable and useful central estimates
	#' compared to a mean or a median.
	#' https://towardsdatascience.com/on-average-youre-using-the-wrong-average-geometric-harmonic-means-in-data-analysis-2a703e21ea0

	library(dplyr)
	library(tidyr)
	library(ggplot2)


	library(ggplot2)
	library(tidyr)
	library(dplyr)


	# Normalize
	data(mtcars)
	mtcars_norm <- as.data.frame(apply(mtcars, 2, scale))
	# Make long

	# Version 1: LOC incentive --> inflated code
	add_up = function(inputs){
	total = inputs[1]

	for i in 2:length(inputs){
	total = total + inputs[i]
	}

	return(total)
	}

	def cs_service_bot():
	welcome_message = """Hello! Welcome to the DNS Cable Company's Service Portal. Are you a new or existing customer?
	\n[1] New Customer
	\n[2] Existing Customer
	\n"""

	response = input(welcome_message)

	if response == "1":
	new_customer()

	rm(list=ls())
	library(quantmod)
	library(lubridate)
	library(PerformanceAnalytics)

	#' Required 'drawdown' size
	#' Default: -6% return
	drawdownHurdle<- -0.06

	# Grab data -----------------------------------------------------------------------------------

	effFrontier = function (data, nports = 20, shorts=T,wmin=0, wmax=1)
	{
	rcov<-cov(data)
	averet<-colMeans(data)
	mxret = max((colMeans(data)))
	mnret = 0#-mxret Long only...
	n.assets = ncol(data)
	reshigh = rep(wmax,n.assets)
	if( shorts )
	{