Mark Edmondson MarkEdmondson1234

## google_analytics_bigquery_user_mapping_table_customer.sql
  -- Author: Krisjan Oldekamp
  -- https://stacktonic.com/article/create-a-user-mapping-table-based-on-the-google-analytics-4-big-query-dataset
DECLARE
  lookback_window INT64 DEFAULT 90; -- How many days to lookback into the dataset to search for IDs (compared to today)
  -- Deduplicate array of struct
CREATE TEMP FUNCTION
  DEDUP(val ANY TYPE) AS ((
    SELECT
      ARRAY_AGG(t)
    FROM (

## AWS-furrr.R
# This example demonstrates running furrr code distributed on 2 AWS instances ("nodes").

# The instances have already been created.

library(future)
library(furrr)

# Two t2.micro AWS instances
# Created from http://www.louisaslett.com/RStudio_AMI/
public_ip <- c("34.205.155.182", "34.201.26.217")

## AdobeAnalytics-GovernanceExport.R
library("RSiteCatalyst")
library("dplyr")

SCAuth("peter.meyer@xxx.com:xxx", "xxx")

reportSuites <- GetReportSuites()

evar <- GetEvars(reportSuites$rsid) #%>%
#  reportSuite <- reportSuites$rsid


## global.R
library(googleAuthR)
library(shiny)
library(shinyjs)

## app.R
library(shiny)

# WARNING: This sketch does not make proper use of the "state" parameter.
# Doing so usually involves using cookies, which can be done with the
# Rook package but I have not done that here. If you choose to use this
# approach in production, please check the state parameter properly!

APP_URL <- if (interactive()) {
  # This might be useful for local development. If not, just hardcode APP_URL
  # to the deployed URL that you'll provide a few lines below.

## knit_cloudstorage.rmd
---
title: "Host image files on Google Cloud storage"
author: "Michael Whitaker"
date: "January 12, 2017"
output:
    html_document:
        self_contained: false
---

```{r setup, include=FALSE}

## visgreatlessfilling.r
# devtools::install_github("hrbrmstr/vegalite")
library(vegalite)
library(htmltools)

dat <- jsonlite::fromJSON('[
      {"a": "A","b": 28}, {"a": "B","b": 55}, {"a": "C","b": 43},
      {"a": "D","b": 91}, {"a": "E","b": 81}, {"a": "F","b": 53},
      {"a": "G","b": 19}, {"a": "H","b": 87}, {"a": "I","b": 52}
    ]')

## japan_pyramid.R
library(idbr) # devtools::install_github('walkerke/idbr')
library(ggplot2)
library(animation)
library(dplyr)
library(ggthemes)

idb_api_key("Your Census API key goes here")

male <- idb1('JA', 2010:2050, sex = 'male') %>%
  mutate(POP = POP * -1,

## costdata.gs
function uploadData() {
  var accountId = "xxxxxxxx";
  var webPropertyId = "UA-xxxxxxxx-x";
  var customDataSourceId = "xxxxxxxx";
  var ss = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();
  var maxRows = ss.getLastRow();
  var maxColumns = ss.getLastColumn();
  var data = [];
  for (var i = 1; i < maxRows;i++) {
    data.push(ss.getRange([i], 1,1, maxColumns).getValues());

## animate.R
library(ggraph)
library(gganimate)
library(igraph)
# Data from http://konect.uni-koblenz.de/networks/sociopatterns-infectious
infect <- read.table('out.sociopatterns-infectious', skip = 2, sep = ' ', stringsAsFactors = FALSE)
infect$V3 <- NULL
names(infect) <- c('from', 'to', 'time')
infect$timebins <- as.numeric(cut(infect$time, breaks = 100))

# We want that nice fading effect so we need to add extra data for the trailing
	-- Author: Krisjan Oldekamp
	-- https://stacktonic.com/article/create-a-user-mapping-table-based-on-the-google-analytics-4-big-query-dataset
	DECLARE
	lookback_window INT64 DEFAULT 90; -- How many days to lookback into the dataset to search for IDs (compared to today)
	-- Deduplicate array of struct
	CREATE TEMP FUNCTION
	DEDUP(val ANY TYPE) AS ((
	SELECT
	ARRAY_AGG(t)
	FROM (
	# This example demonstrates running furrr code distributed on 2 AWS instances ("nodes").

	# The instances have already been created.

	library(future)
	library(furrr)

	# Two t2.micro AWS instances
	# Created from http://www.louisaslett.com/RStudio_AMI/
	public_ip <- c("34.205.155.182", "34.201.26.217")
	library("RSiteCatalyst")
	library("dplyr")

	SCAuth("peter.meyer@xxx.com:xxx", "xxx")

	reportSuites <- GetReportSuites()

	evar <- GetEvars(reportSuites$rsid) #%>%
	# reportSuite <- reportSuites$rsid
	library(shiny)

	# WARNING: This sketch does not make proper use of the "state" parameter.
	# Doing so usually involves using cookies, which can be done with the
	# Rook package but I have not done that here. If you choose to use this
	# approach in production, please check the state parameter properly!

	APP_URL <- if (interactive()) {
	# This might be useful for local development. If not, just hardcode APP_URL
	# to the deployed URL that you'll provide a few lines below.
	---
	title: "Host image files on Google Cloud storage"
	author: "Michael Whitaker"
	date: "January 12, 2017"
	output:
	html_document:
	self_contained: false
	---

	```{r setup, include=FALSE}
	# devtools::install_github("hrbrmstr/vegalite")
	library(vegalite)
	library(htmltools)

	dat <- jsonlite::fromJSON('[
	{"a": "A","b": 28}, {"a": "B","b": 55}, {"a": "C","b": 43},
	{"a": "D","b": 91}, {"a": "E","b": 81}, {"a": "F","b": 53},
	{"a": "G","b": 19}, {"a": "H","b": 87}, {"a": "I","b": 52}
	]')
	library(idbr) # devtools::install_github('walkerke/idbr')
	library(ggplot2)
	library(animation)
	library(dplyr)
	library(ggthemes)

	idb_api_key("Your Census API key goes here")

	male <- idb1('JA', 2010:2050, sex = 'male') %>%
	mutate(POP = POP * -1,
	function uploadData() {
	var accountId = "xxxxxxxx";
	var webPropertyId = "UA-xxxxxxxx-x";
	var customDataSourceId = "xxxxxxxx";
	var ss = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();
	var maxRows = ss.getLastRow();
	var maxColumns = ss.getLastColumn();
	var data = [];
	for (var i = 1; i < maxRows;i++) {
	data.push(ss.getRange([i], 1,1, maxColumns).getValues());
	library(ggraph)
	library(gganimate)
	library(igraph)
	# Data from http://konect.uni-koblenz.de/networks/sociopatterns-infectious
	infect <- read.table('out.sociopatterns-infectious', skip = 2, sep = ' ', stringsAsFactors = FALSE)
	infect$V3 <- NULL
	names(infect) <- c('from', 'to', 'time')
	infect$timebins <- as.numeric(cut(infect$time, breaks = 100))

	# We want that nice fading effect so we need to add extra data for the trailing