akanik

function getMailChimpData(){
  
  // Here are the things you will change
  var API_KEY = 'YOUR-KEY-HERE';
  var MEMBER_LIST_ID = 'LIST-ID-WITH-SEGMENTS';
  var KYCIR_LIST_ID = 'LIST-ID-WITH-NO-SEGMENTS';
  
  function calculateAvgRates(runType, segmentID, rateType){
    var ratesList = [];
    

akanik

# Equation looks to see if there are ties, if ties exist,
# then it skips the next ranking number so your last ranking 
# number corresponds with the actual number of actual things 
# you're ranking.

# This equation allows for up to a 4-way tie.

# Column E holds the values you're comparing to create the
# rank and Column F is where you're putting this equation

akanik

//These two functions create a new menu item titled "Update data" that
//when clicked will run the rest of the code we're writing here
function onOpen() {
  var ui = SpreadsheetApp.getUi();
  ui.createMenu('Update data')
      .addItem('Update data', 'updateDataMenu')
      .addToUi();
}

function updateDataMenu() {

akanik

function gaDateFetch(){
  // Here are all the variables you'll need to set
  var sheetName = 'by-date';
  var viewId = 'ga:xxxxxxx';
  var metric = 'ga:users';

  // select the sheet named by-date
  var ss = SpreadsheetApp.getActiveSpreadsheet();
  var sheet = ss.getSheetByName(sheetName);
  

akanik

#https://stackoverflow.com/questions/19914937/applying-function-with-multiple-arguments-to-create-a-new-pandas-column

def float_to_datetime(ddate, ttime):
    return pd.to_datetime('1899-12-30') + pd.to_timedelta(ddate + ttime),'s')
                        
response_data['pickup_datetime'] = np.vectorize(float_to_datetime)(response_data['date'], response_data['911_pickup_time'])
response_data['dispatch_datetime'] = np.vectorize(float_to_datetime)(response_data['date'], response_data['dipatch_time'])
response_data['arrive_datetime'] = np.vectorize(float_to_datetime)(response_data['date'], response_data['arrive_time'])

akanik

#https://gist.github.com/oag335/9959241
response_data['real_date'] = pd.to_datetime('1899-12-30') + pd.to_timedelta(response_data['date'],'D')

akanik

# https://www.commandlinefu.com/commands/view/9002/extracting-a-range-of-pages-from-a-pdf-using-ghostscript
# commandline
gs -sDEVICE=pdfwrite -dNOPAUSE -dBATCH -dSAFER -dFirstPage=14 -dLastPage=17 -sOutputFile=OUTPUT.pdf ORIGINAL.pdf

akanik

import os

data_dir = '/Users/akanik/data/csv/'
file1 = 'whatever-data-1.csv'
file1_path = data_dir + file1
#Make sure your combined file does not live within your data_dir.
#This will cause an endless loop of writing
combined_file = '/Users/akanik/data/whatever-data-ALL.csv'

fout = open(combined_file,'a')

akanik

=if(isblank(B2),A1,B2)

akanik

#virtual environment
>> cd [project-path]
>> mkvirtualenv -a ./ [-r requirements_file] ENVNAME

#install django in virtualenv
>> pip install Django

#create django project
>> django-admin startproject mysite