Manos Parzakonis IronistM

## forecasting_examples_hyndman.r
require(fpp)
# Please make sure at least v3.10 of the forecast is loaded
# before running these examples.

# Three examples
beer <- aggregate(ausbeer)
plot(beer)
plot(a10)
plot(taylor)

## save an R dataframe with the name specified by a string.r
# Create explicit data frames and TS objects given a list
market.list<- c("GR","CY","RU","RO","PL","UA","ROW")
for (i in market.list) {
  tmp <- subset(data,Market==i)
  tmp<-ts(tmp) # It's a timeseries afterall...
  # Let's save the data somewhere so we don't get back all the time
  filename <- paste("data_", i, sep="")
  assign(filename, tmp)
  save(filename, file=paste(filename, ".rda",sep=""))
}

## facebookads.gs
var SPREADSHEET_URL = "";
function facebookSpend() {
  var ss = SpreadsheetApp.openByUrl(SPREADSHEET_URL);
  var sheet = ss.getSheetByName('facebook');
  var values = [];
  Utilities.sleep(1000);
  var fullUrl = 'https://graph.facebook.com/v2.3/act_xxx/stats?access_token=xxx';
  var fetchRequest = UrlFetchApp.fetch(fullUrl);
  var results = JSON.parse(fetchRequest.getContentText());
  Logger.log(results.spent/100);

## track_email_opens.js
/*

    Email Tracking with Google Analytics
    ====================================

    Written by Amit Agarwal on 09/24/2013

    Tutorial: http://labnol.org/?p=8082
    YouTube : http://youtu.be/9T_EqwQnZY0
    Support : http://twitter.com/labnol

## Termux.Jupyter.md

      
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                IronistM
                / Termux.Jupyter.md
            
            
              Created
              January 3, 2018 12:26
                — forked from pcornier/Termux.Jupyter.md
            
              
                Install Jupyter with Numpy, SciPy, Pandas and Matplotlib
              
          
    pkg install apt-transport-https curl gnupg pkg-config clang
pkg install freetype freetype-dev libpng libpng-dev libzmq-dev libzmq

mkdir $PREFIX/etc/apt/sources.list.d

echo "deb [trusted=yes] https://its-pointless.github.io/files/ termux extras" > $PREFIX/etc/apt/sources.list.d/pointless.list

curl -O https://its-pointless.github.io/pointless.gpg


## 3G-fraction-1s-example.sql
SELECT
  SUM(fcp.density)
FROM
  `chrome-ux-report.chrome_ux_report.201710`,
  UNNEST(first_contentful_paint.histogram.bin) AS fcp
WHERE
  origin = "https://www.google.co.in"
  AND effective_connection_type.name = "3G"
  AND fcp.END <= 1000

## quakes.R
library(ggplot2)
library(ggmap)
library(plyr)
library(grid)
library(gridExtra)

# read in cleaned up data
dat <- read.table("quakes.dat", header=TRUE, stringsAsFactors=FALSE)

# map decimal magnitudes into an integer range

## dynamically_changing_SQL_statement.qvs
let vLastMonth = Year(AddMonths(now(),-1)) & '-' & num(month(addmonths(now(),-1)),'00') & '-01';
// This gets the first of the previous month
let vThisMonth = Year(now()) & '-' & num(month(now()),'00') & '-01';
// This gets the first of the current month

ODBC CONNECT TO MyDSN; // Change to your database

LOAD *;

SQL SELECT

## random_data_generation.txt
set RecCount = 500000000; // Number of records to generate

Data:
load
    chr(round(25 * rand() + 65)) & chr(round(25 * rand() + 65)) & chr(round(25 * rand() + 65)) as Customer, // Customer name between AAA and ZZZ
    chr(round(25 * rand() + 65)) as Product,                // Product name between A and Z
    round(3 * Rand() + 2008) as Year,                  // Year between 2008 and 2011
    round(1000000 * Rand()) as Actual,                  // Actual Revenue between 0 and 1,000,000
    round(1000000 * Rand()) as Target                  // Target Revenue between 0 and 1,000,000
autogenerate(RecCount);

## keybase.md

      
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                IronistM
                / keybase.md
            
            
              Created
              October 5, 2017 13:45
            
          
    Keybase proof

I hereby claim:

I am ironistm on github.
I am ironistm (https://keybase.io/ironistm) on keybase.
I have a public key ASCZ7BiBXH6ory2tLDfrhyxX7Cpsmr-M5343erNPTYUqlQo

To claim this, I am signing this object:
	require(fpp)
	# Please make sure at least v3.10 of the forecast is loaded
	# before running these examples.

	# Three examples
	beer <- aggregate(ausbeer)
	plot(beer)
	plot(a10)
	plot(taylor)
	# Create explicit data frames and TS objects given a list
	market.list<- c("GR","CY","RU","RO","PL","UA","ROW")
	for (i in market.list) {
	tmp <- subset(data,Market==i)
	tmp<-ts(tmp) # It's a timeseries afterall...
	# Let's save the data somewhere so we don't get back all the time
	filename <- paste("data_", i, sep="")
	assign(filename, tmp)
	save(filename, file=paste(filename, ".rda",sep=""))
	}
	var SPREADSHEET_URL = "";
	function facebookSpend() {
	var ss = SpreadsheetApp.openByUrl(SPREADSHEET_URL);
	var sheet = ss.getSheetByName('facebook');
	var values = [];
	Utilities.sleep(1000);
	var fullUrl = 'https://graph.facebook.com/v2.3/act_xxx/stats?access_token=xxx';
	var fetchRequest = UrlFetchApp.fetch(fullUrl);
	var results = JSON.parse(fetchRequest.getContentText());
	Logger.log(results.spent/100);
	/*

	Email Tracking with Google Analytics
	====================================

	Written by Amit Agarwal on 09/24/2013

	Tutorial: http://labnol.org/?p=8082
	YouTube : http://youtu.be/9T_EqwQnZY0
	Support : http://twitter.com/labnol
	SELECT
	SUM(fcp.density)
	FROM
	`chrome-ux-report.chrome_ux_report.201710`,
	UNNEST(first_contentful_paint.histogram.bin) AS fcp
	WHERE
	origin = "https://www.google.co.in"
	AND effective_connection_type.name = "3G"
	AND fcp.END <= 1000
	library(ggplot2)
	library(ggmap)
	library(plyr)
	library(grid)
	library(gridExtra)

	# read in cleaned up data
	dat <- read.table("quakes.dat", header=TRUE, stringsAsFactors=FALSE)

	# map decimal magnitudes into an integer range
	let vLastMonth = Year(AddMonths(now(),-1)) & '-' & num(month(addmonths(now(),-1)),'00') & '-01';
	// This gets the first of the previous month
	let vThisMonth = Year(now()) & '-' & num(month(now()),'00') & '-01';
	// This gets the first of the current month

	ODBC CONNECT TO MyDSN; // Change to your database

	LOAD *;

	SQL SELECT
	set RecCount = 500000000; // Number of records to generate

	Data:
	load
	chr(round(25 * rand() + 65)) & chr(round(25 * rand() + 65)) & chr(round(25 * rand() + 65)) as Customer, // Customer name between AAA and ZZZ
	chr(round(25 * rand() + 65)) as Product, // Product name between A and Z
	round(3 * Rand() + 2008) as Year, // Year between 2008 and 2011
	round(1000000 * Rand()) as Actual, // Actual Revenue between 0 and 1,000,000
	round(1000000 * Rand()) as Target // Target Revenue between 0 and 1,000,000
	autogenerate(RecCount);