RSiteCatalyst Version 1.4.8 Release Notes

For being in RSiteCatalyst retirement, I’m ending up working on more functionality lately ¯_(ツ)_/¯. Here are the changes for RSiteCatalyst 1.4.8, which should be available on CRAN shortly:

Segment Stacking

RSiteCatalyst now has the ability to take multiple values in the segment.id keyword for the Queue* functions. This functionality was graciously provided by Adam Gitzes, closing an issue that was nearly a year old. At times it felt like I was hazing him with change requests, but for Adam’s first open-source contribution, this is a huge addition in functionality.

So now you are able to pass multiple segments into a function call and get an ‘AND’ behavior like so:

1
2
3
4
5
6
7
stacked_seg <- QueueRanked("zwitchdev",
                          "2016-03-08",
                          "2016-03-09",
                          "pageviews",
                          "page",
                          segment.id = c("5433e4e6e4b02df70be4ac63", "54adfe3de4b02df70be5ea08")
                          )

The result (Visits from Social AND Visits from Apple Browsers):

rsitecatalyst-segment-stacking

QueueSummary: Now with date.to and date.from keywords

In response to GitHub issue #158, date.to and date.from parameters were added; this was a minor, but long-term oversight (it’s always been possible to do this in the Adobe Analytics API). So now rather than just specifying the date keyword and getting a full-year summary or a full-month, you can specify any arbitrary start/end dates.

Trivial Fixes: Silenced httr message, clarified documentation

Starting with the newest version of httr, you get a message for any API call where the encoding wasn’t set. So for long running Queue* requests, you may have received dozens of warnings to stdout about "No encoding supplied: defaulting to UTF-8." This has been remedied, and the warning should no longer occur.

Also, the documentation for the Queue* functions was clarified to show an example of using SAINT classifications as the report breakdown; hopefully this didn’t cause too much confusion to anyone else.

Volunteers Wanted!

As I referenced in the first paragraph, while I’m fully committed to maintaining RSiteCatalyst, I don’t currently have the time/desire to continue to develop the package to improve functionality. Given that I don’t use this package for my daily work, it’s hard for me to dedicate time to the project.

Thanks again to Adam Gitzes who stepped up and provided significant effort to close an outstanding feature request. I would love if others in the digital analytics community would follow Adam’s lead; don’t worry about whether you are ‘good enough’, get a working solution together and we’ll figure out how to harden the code and get it merged. Be the code change you want to see the world 🙂

  • RSiteCatalyst Version 1.4.16 Release Notes
  • Using RSiteCatalyst With Microsoft PowerBI Desktop
  • RSiteCatalyst Version 1.4.14 Release Notes
  • RSiteCatalyst Version 1.4.13 Release Notes
  • RSiteCatalyst Version 1.4.12 (and 1.4.11) Release Notes
  • Self-Service Adobe Analytics Data Feeds!
  • RSiteCatalyst Version 1.4.10 Release Notes
  • WordPress to Jekyll: A 30x Speedup
  • Bulk Downloading Adobe Analytics Data
  • Adobe Analytics Clickstream Data Feed: Calculations and Outlier Analysis
  • Adobe: Give Credit. You DID NOT Write RSiteCatalyst.
  • RSiteCatalyst Version 1.4.8 Release Notes
  • Adobe Analytics Clickstream Data Feed: Loading To Relational Database
  • Calling RSiteCatalyst From Python
  • RSiteCatalyst Version 1.4.7 (and 1.4.6.) Release Notes
  • RSiteCatalyst Version 1.4.5 Release Notes
  • Getting Started: Adobe Analytics Clickstream Data Feed
  • RSiteCatalyst Version 1.4.4 Release Notes
  • RSiteCatalyst Version 1.4.3 Release Notes
  • RSiteCatalyst Version 1.4.2 Release Notes
  • Destroy Your Data Using Excel With This One Weird Trick!
  • RSiteCatalyst Version 1.4.1 Release Notes
  • Visualizing Website Pathing With Sankey Charts
  • Visualizing Website Structure With Network Graphs
  • RSiteCatalyst Version 1.4 Release Notes
  • Maybe I Don't Really Know R After All
  • Building JSON in R: Three Methods
  • Real-time Reporting with the Adobe Analytics API
  • RSiteCatalyst Version 1.3 Release Notes
  • Adobe Analytics Implementation Documentation in 60 Seconds
  • RSiteCatalyst Version 1.2 Release Notes
  • Clustering Search Keywords Using K-Means Clustering
  • RSiteCatalyst Version 1.1 Release Notes
  • Anomaly Detection Using The Adobe Analytics API
  • (not provided): Using R and the Google Analytics API
  • My Top 20 Least Useful Omniture Reports
  • For Maximum User Understanding, Customize the SiteCatalyst Menu
  • Effect Of Modified Bounce Rate In Google Analytics
  • Adobe Discover 3: First Impressions
  • Using Omniture SiteCatalyst Target Report To Calculate YOY growth
  • ODSC webinar: End-to-End Data Science Without Leaving the GPU
  • PyData NYC 2018: End-to-End Data Science Without Leaving the GPU
  • Data Science Without Leaving the GPU
  • Getting Started With OmniSci, Part 2: Electricity Dataset
  • Getting Started With OmniSci, Part 1: Docker Install and Loading Data
  • Parallelizing Distance Calculations Using A GPU With CUDAnative.jl
  • Building a Data Science Workstation (2017)
  • JuliaCon 2015: Everyday Analytics and Visualization (video)
  • Vega.jl, Rebooted
  • Sessionizing Log Data Using data.table [Follow-up #2]
  • Sessionizing Log Data Using dplyr [Follow-up]
  • Sessionizing Log Data Using SQL
  • Review: Data Science at the Command Line
  • Introducing Twitter.jl
  • Code Refactoring Using Metaprogramming
  • Evaluating BreakoutDetection
  • Creating A Stacked Bar Chart in Seaborn
  • Visualizing Analytics Languages With VennEuler.jl
  • String Interpolation for Fun and Profit
  • Using Julia As A "Glue" Language
  • Five Hard-Won Lessons Using Hive
  • Using SQL Workbench with Apache Hive
  • Getting Started With Hadoop, Final: Analysis Using Hive & Pig
  • Quickly Create Dummy Variables in a Data Frame
  • Using Amazon EC2 with IPython Notebook
  • Adding Line Numbers in IPython/Jupyter Notebooks
  • Fun With Just-In-Time Compiling: Julia, Python, R and pqR
  • Getting Started Using Hadoop, Part 4: Creating Tables With Hive
  • Tabular Data I/O in Julia
  • Hadoop Streaming with Amazon Elastic MapReduce, Python and mrjob
  • A Beginner's Look at Julia
  • Getting Started Using Hadoop, Part 3: Loading Data
  • Innovation Will Never Be At The Push Of A Button
  • Getting Started Using Hadoop, Part 2: Building a Cluster
  • Getting Started Using Hadoop, Part 1: Intro
  • Instructions for Installing & Using R on Amazon EC2
  • Video: SQL Queries in R using sqldf
  • Video: Overlay Histogram in R (Normal, Density, Another Series)
  • Video: R, RStudio, Rcmdr & rattle
  • Getting Started Using R, Part 2: Rcmdr
  • Getting Started Using R, Part 1: RStudio
  • Learning R Has Really Made Me Appreciate SAS