Sudev sudevschiz

## latlong.gs
function findLatLong() {
  Logger.log(SpreadsheetApp.getActive());
  var sheet = SpreadsheetApp.getActiveSheet();
  var range = sheet.getDataRange();

  var numRows = range.getNumRows();
  var numCols = range.getNumColumns();
  for (var i = 2; i <= numRows; i++) {
         var locality = range.getCell(i,1).getValue();


## filehandling.sh
for file in *.jpg;
do
file ${file%*};

convert -crop 300x300+300+80 $file cropped/$file;

#do whatever you want. The filename is in the $file variable.

done

## post.html
---
---
<!DOCTYPE html>
<html>
  {% include head.html %}
  <body itemscope itemtype="http://schema.org/Article">
<script>
  window.fbAsyncInit = function() {
    FB.init({
      appId      : '364481490395389',

## enstoncbi_convert.R
  ##If using for the first time, source the below packages

# source("https://bioconductor.org/biocLite.R")
# biocLite("org.Mm.eg.db")

##Load the db to the environment

library("org.Mm.eg.db")

## The list of EnsEMBL Gene IDs are stored in a file "ens.txt". Read the text file as a table

## Code.gs
function findLatLong() {
  var sheet = SpreadsheetApp.getActiveSheet();
  SpreadsheetApp.getUi().alert('Hello, world!');
  var startRow = 2;  // First row of data to process
  var numRows = 2;   // Number of rows to process
  // Fetch the range of cells A2:B3
  var dataRange = sheet.getRange(startRow, 2, numRows, 2)
  // Fetch values for each row in the Range.
  var data = dataRange.getValues();
  for (i in data) {

## convert_binary.py
import csv


#Specify start and end values in decimal
range_start = 1
range_stop  = 2^15


with open('output_file.csv','w') as out_file:

## string_manipulation.py
out_file = open("out_file.txt","w")

with open('formulas.txt','r') as fil:
    for lin in fil:
        #Here, '+' is the unwanted character at the 0th position. Edit accordingly for other characters
        if(lin[0] == "+"):
            new_line = lin[1:]
            print new_line

        else:

## split_data.R
## Function to split the dataframe
## 143 is just a default seed

splitdf <- function(dataframe, seed=143,splitper) {
  if (!is.null(seed)) set.seed(seed)
  index <- 1:nrow(dataframe)
  trainindex <- sample(index, (splitper/100)*trunc(length(index)))
  trainset <- dataframe[trainindex, ]
  testset <- dataframe[-trainindex, ]
  list(trainset=trainset,testset=testset)

## sapply_eg.R
## Supposed you want to apply an operation to every element in a vector. Efficient way to do it in R is to use sapply / lapply

## Sample vector of 100 observation
x_vec <- rnorm(100)

## Need to find the absolute value of each element

x_abs <- sapply(x_vec,abs)

## The above implementation equivalent to doing x_abs <- abs(x_vec)

## email_utility.py
import smtplib
from os.path import basename
from email.mime.application import MIMEApplication
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.utils import COMMASPACE, formatdate
import sys
import datetime
import json
	function findLatLong() {
	Logger.log(SpreadsheetApp.getActive());
	var sheet = SpreadsheetApp.getActiveSheet();
	var range = sheet.getDataRange();

	var numRows = range.getNumRows();
	var numCols = range.getNumColumns();
	for (var i = 2; i <= numRows; i++) {
	var locality = range.getCell(i,1).getValue();
	for file in *.jpg;
	do
	file ${file%*};

	convert -crop 300x300+300+80 $file cropped/$file;

	#do whatever you want. The filename is in the $file variable.

	done
	---
	---
	<!DOCTYPE html>
	<html>
	{% include head.html %}
	<body itemscope itemtype="http://schema.org/Article">
	<script>
	window.fbAsyncInit = function() {
	FB.init({
	appId : '364481490395389',
	##If using for the first time, source the below packages

	# source("https://bioconductor.org/biocLite.R")
	# biocLite("org.Mm.eg.db")

	##Load the db to the environment

	library("org.Mm.eg.db")

	## The list of EnsEMBL Gene IDs are stored in a file "ens.txt". Read the text file as a table
	function findLatLong() {
	var sheet = SpreadsheetApp.getActiveSheet();
	SpreadsheetApp.getUi().alert('Hello, world!');
	var startRow = 2; // First row of data to process
	var numRows = 2; // Number of rows to process
	// Fetch the range of cells A2:B3
	var dataRange = sheet.getRange(startRow, 2, numRows, 2)
	// Fetch values for each row in the Range.
	var data = dataRange.getValues();
	for (i in data) {
	import csv


	#Specify start and end values in decimal
	range_start = 1
	range_stop = 2^15



	with open('output_file.csv','w') as out_file:
	out_file = open("out_file.txt","w")

	with open('formulas.txt','r') as fil:
	for lin in fil:
	#Here, '+' is the unwanted character at the 0th position. Edit accordingly for other characters
	if(lin[0] == "+"):
	new_line = lin[1:]
	print new_line

	else:
	## Function to split the dataframe
	## 143 is just a default seed

	splitdf <- function(dataframe, seed=143,splitper) {
	if (!is.null(seed)) set.seed(seed)
	index <- 1:nrow(dataframe)
	trainindex <- sample(index, (splitper/100)*trunc(length(index)))
	trainset <- dataframe[trainindex, ]
	testset <- dataframe[-trainindex, ]
	list(trainset=trainset,testset=testset)
	## Supposed you want to apply an operation to every element in a vector. Efficient way to do it in R is to use sapply / lapply

	## Sample vector of 100 observation
	x_vec <- rnorm(100)

	## Need to find the absolute value of each element

	x_abs <- sapply(x_vec,abs)

	## The above implementation equivalent to doing x_abs <- abs(x_vec)
	import smtplib
	from os.path import basename
	from email.mime.application import MIMEApplication
	from email.mime.multipart import MIMEMultipart
	from email.mime.text import MIMEText
	from email.utils import COMMASPACE, formatdate
	import sys
	import datetime
	import json