Title: Project Title Author: First Last Email: [email protected] Address: 1234 Street, City, State 12345 Phone: (XXX)XXX-XXXX Affiliation: www.LaCroixDesign.net Copyright: 2015 Company Name Keywords: Proposal, Web Design Date: March 13, 2015
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library(shiny) | |
library(datasets) | |
Logged = FALSE; | |
PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad") | |
# Define server logic required to summarize and view the selected dataset | |
shinyServer(function(input, output) { | |
source("www/Login.R", local = TRUE) | |
observe({ | |
if (USER$Logged == TRUE) { |
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library(shiny) | |
library(dplyr) | |
library(lubridate) | |
# Load libraries and functions needed to create SQLite databases. | |
library(RSQLite) | |
library(RSQLite.extfuns) | |
saveSQLite <- function(data, name){ | |
path <- dplyr:::db_location(filename=paste0(name, ".sqlite")) |
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# Here are a few methods for getting text from PDF files. Do read through | |
# the instructions carefully! NOte that this code is written for Windows 7, | |
# slight adjustments may be needed for other OSs | |
# Tell R what folder contains your 1000s of PDFs | |
dest <- "G:/somehere/with/many/PDFs" | |
# make a vector of PDF file names | |
myfiles <- list.files(path = dest, pattern = "pdf", full.names = TRUE) |
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#!/usr/bin/env python3 | |
import boto3, argparse | |
parser = argparse.ArgumentParser() | |
parser.add_argument('-b','--bucket', help='Name of your S3 Bucket', required=True) | |
parser.add_argument('-o','--object', help='Name of the object + prefix in your bucket', required=True) | |
parser.add_argument('-t','--time', type=int, help='Expirery in seconds Default = 60', default=60) | |
args = vars(parser.parse_args()) |
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getSymbols("^GSPC", from="1950-01-01") | |
p = 10 | |
a = na.omit(merge( volatility(GSPC, n=p)*100, lag(volatility(GSPC, n=p), k=-p)*100 )) | |
names(a) = c("hv", "rv") | |
medianvalues = c() | |
meanvalues = c() | |
maxvalues = c() | |
minvalues = c() | |
keys = c() | |
for ( x in seq( 0, max(a$hv), 2 ) ) |
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llxc = function( a, ll=-12:12, legend.loc="topleft", displayLegend=T, legend.cex=1.0, overplot=F ) | |
{ | |
if ( ncol(a) < 2 ) | |
{ | |
print( "Not enough columns") | |
return; | |
} | |
a = na.omit(a) | |
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import simplejson as json | |
import requests | |
#your spreadsheet key here. I'm using an example from the Victorian election campaign | |
key = "1THJ6MgfEk-1egiPFeDuvs4qEi02xTpz4fq9RtO7GijQ" | |
#google api request urls - I'm doing the first one just to get nice key values (there's probably a better way to do this) | |
url1 = "https://spreadsheets.google.com/feeds/cells/" + key + "/od6/public/values?alt=json" |
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'use strict'; | |
var domain = require('domain'); | |
var userMethod = 'handler'; | |
var userCodeWrapper = function(userCode) { | |
return '\ | |
"use strict";\n\ | |
' + userCode + '\n\ | |
try {\n\ |
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library(shiny) | |
library(rmarkdown) | |
shinyServer(function(input, output) { | |
output$html = reactive({ | |
t <- tempfile() | |
cat(input$markdown, file = t) |