zjuul

-- this query outputs a data visualisation to explore how many unique products people
-- see on your website, and the conversion rate

-- it uses Big Query SQL on a GA4Dataform events table - check https://github.com/superformlabs/ga4dataform-community

with products_per_user as (
  SELECT
    user_pseudo_id,
    count( distinct if(event_name = 'view_item', i.item_name, NULL) ) as n_items_viewed,
    max( if(event_name = 'purchase', 1, 0)) as purchaser 

SiegHartR

library(googleAuthR)
library(googleAnalyticsR)
library(tidyverse)
library(bigQueryR)
library(rvest)
library(lubridate)

# Last Financial Week
end_date <- floor_date(Sys.Date(),"week") - 1
start_date <- end_date - 6

hitGovernor

(function () {
  // gets hotjar user id (hjUID)
  var hjUID = "";
  try {
    if (typeof (hj) != "undefined" && hj.hasOwnProperty("globals")) {
      // sample: a21c0a02-3b48-53c6-94b4-5604e281e5d8
      // the value before the first "-" ("a21c0a02") is the user identifier that can be referenced in the hj interface
      // use the following snippet to return only the user identifier (eg// "a21c0a02"): 
      // hjUID =hj.globals.get("userId").split("-").shift();

filippchistiakov

/**
 * Unpivot a pivot table of any size.
 *
 * @param {A1:D30} data The pivot table.
 * @param {1} fixColumns Number of columns, after which pivoted values begin. Default 1.
 * @param {1} fixRows Number of rows (1 or 2), after which pivoted values begin. Default 1.
 * @param {"city"} titlePivot The title of horizontal pivot values. Default "column".
 * @param {"distance"[,...]} titleValue The title of pivot table values. Default "value".
 * @return The unpivoted table
 * @customfunction

pshapiro

iconifyit

# ############################### #
#        A/B TESTING (START)      #
# ############################### #

# (1) Check if our cookie is already set. 
#     If so, redirect to the previously-viewed page.

RewriteCond %{HTTP_COOKIE} ab_test_vers=([^;]+)
RewriteRule ^THE-PAGE-BEING-TESTED$ HTTP://YOUR-DOMAIN.COM/tracking/%1 [cookie=ab_test_vers_match:true:YOUR-DOMAIN.COM,L]

rudeboybert

# R source code for all slides/videos in Albert Y. Kim's "Modeling with Data in
# the Tidyverse" DataCamp course:
# https://www.datacamp.com/courses/modeling-with-data-in-the-tidyverse
# This code is available at http://bit.ly/modeling_tidyverse

# Load all necessary packages -----
library(ggplot2)
library(dplyr)
library(moderndive)

pshapiro

library("igraph")
# Swap out path to your Screaming Frog All Outlink CSV. For Windows, remember to change backslashes to forward slashes.
links <- read.csv("C:/Documents/screaming-frog-all-outlinks.csv", skip = 1) # CSV Path
# This line of code is optional. It filters out JavaScript, CSS, and Images. Technically you should keep them in there.
links <- subset(links, Type=="AHREF") # Optional line. Filter.
links <- subset(links, Follow=="true")
links <- subset(links, select=c(Source,Destination))
g <- graph.data.frame(links)
pr <- page.rank(g, algo = "prpack", vids = V(g), directed = TRUE, damping = 0.85)
values <- data.frame(pr$vector)

derekmartinla

/**********************************************************************************************************************
* Amazon Autocomplete Tool 
* Leverage the Amazon Autocomplete feature to find highly commercial keyword opportunities.
* Export the results for efficient importing into Google Adwords 
* Version 1.0
* Created By: Derek Martin
* DerekMartinLA.com or MixedMarketingArtist.com
**********************************************************************************************************************/

 var hashMapResults = {}; 

dmarx

#install.packages("rjson","RCurl")
library(RCurl)
library(rjson)

get_User_subs_page = function(user, after=NULL, cache=c()){
  
  baseurl = "http://www.reddit.com/user/"
  params = "limit=100"
  if(!is.null(after)){    
    params = paste(params, "&after=",after, sep="")