33sticks

/* Loads IFrame Player API Code asynchronously */
var tag = document.createElement('script');
tag.src = "https://www.youtube.com/iframe_api";
var firstScriptTag = document.getElementsByTagName('script')[0];
firstScriptTag.parentNode.insertBefore(tag, firstScriptTag);

33sticks

/* Media Module Config */
s.enableVideoTracking=true
if(s.enableVideoTracking){
s.loadModule('Media');
s.Media.autoTrack=false;
s.Media.playerName='YouTube';
s.Media.segmentByMilestones=true;
s.Media.trackMilestones='25,50,75';
s.Media.trackUsingContextData=true;
s.Media.contextDataMapping = {

33sticks

/*YouTube Player updates required by Adobe Video Tracking module */
var n=0;

jQuery('iframe').each(function() {
 
 var src = jQuery(this).attr('src');
 
if(src){
	if (src.indexOf('youtube.com') > -1) {
     

33sticks

#import the pandas library
import pandas as pd

#pull adobe report download into a dataframe; ignorning the comment header
df = pd.read_csv("/Users/jasonthompson/Documents/analysis/python/sp/adobe_id.csv", comment="#", header=1)

#export cleaned data to a new csv file
df.to_csv("/Users/jasonthompson/Documents/analysis/python/sp/adobe_id_no-comments.csv", encoding='utf-8')

33sticks

# We will use data structures and data analysis tools provided in Pandas library
import pandas as pd

# Import retail sales data from an Excel Workbook into a data frame
path = '/Documents/analysis/python/examples/2015sales.xlsx'
xlsx = pd.ExcelFile(path)
df = pd.read_excel(xlsx, 'Sheet1')

# Let's add a new boolean column to our dataframe that will identify a duplicated order line item (False=Not a duplicate; True=Duplicate)
df['is_duplicated'] = df.duplicated(['order_id', 'order_item_id'])

33sticks

# Load Shiny
library(shiny)

# Define server logic required to request summary data from Adobe Analytics
shinyServer(function(input, output) {

  # Load RSiteCatalyst
  library("RSiteCatalyst")

    # Listen for a click on the 'Get Report Suite Summary' button

33sticks

#import the urlprase library to break url into components
from urlparse import urlparse

#import pandas for data processing
from pandas import DataFrame, Series
import pandas as pd

#import URL data
df = pd.read_csv("/Users/Documents/analysis/my_urls.csv")