psychemedia

# ABOUT:
# A script that grabs a list of the friends or followers of a user on Google+,
# grabs a sample of their friends, and generates the resulting social graph

# USAGE:
# Requirements: networkx (see DEPENDENCIES)
# Configuration: see CONFIGURATION
# Output: files will be save to the reports directory
# To run the script:
# 1) Download this file to a new directory somewhere as eg gplusESPnet.py

timelyportfolio

#obviousness of reits?

#get NAREIT data
#I like NAREIT since I get back to 1971
#much easier though to get Wilshire REIT from FRED
#also it is daily instead of monthly
#getSymbols("WILLREITIND",src="FRED") will do this
require(gdata)
reitURL <- "http://returns.reit.com/returns/MonthlyHistoricalReturns.xls"
reitExcel <- read.xls(reitURL,sheet="Index Data",pattern="All REITs",stringsAsFactors=FALSE)

dsparks

doInstall <- TRUE
toInstall <- c("XML")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

myURL <- "http://en.wikipedia.org/wiki/United_States_presidential_election,_2012"

allTables <- readHTMLTable(myURL)
str(allTables)  # Look at the allTables object to find the specific table we want
stateTable <- allTables[[14]]  # We want the 14th table in the list (maybe 13th?)

dsparks

doInstall <- TRUE
toInstall <- c("zoo")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

ftseIndex <- EuStockMarkets[, 4]
plot(ftseIndex, col = "GRAY")

# Calculate 10-day rolling mean, quickly:
smoothIndex <- rollmean(x = ftseIndex,  # original series

capm

doInstall <- TRUE
toInstall <- c("zoo")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

ftseIndex <- EuStockMarkets[, 4]
plot(ftseIndex, col = "GRAY")

# Calculate 10-day rolling mean, quickly:
smoothIndex <- rollmean(x = ftseIndex,  # original series

pssguy

# load requisite libraries
library(shiny)
library(googleVis) 

# load raw data (NB not provided)
tableByGame <- read.csv("../tableByGame.csv",stringsAsFactors=FALSE)

# to create chart need to repeat one column and get negative of league position as hack
tableByGame$game <- tableByGame$seasonGame
tableByGame$lgPos <- -tableByGame$lgPos

thertrader

###############################################################################
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.

thertrader

############################################################
## Using Genetic Algorithms in Quantitative Trading   
##
## thertrader@gmail.com - Mar 2014
############################################################
library(PerformanceAnalytics)
library(rgenoud)
library(quantmod)
library(TTR)

aniversarioperu

#-*- coding: utf-8 -*-
import codecs
import time
import json
import re
import sys

from selenium import webdriver

mwaskom