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Customizing Click Events: How to Capture and Store Data from JavaScript Objects in R Variables

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Daina Andries
Wednesday, 17 October 2018 / Published in Analytics, Code, Data, Data Science, Data Visualizations, JavaScript, Machine Learning, R, R-Shiny, Tutorials
Interaction Design for Data Exploration Visualizations capable of launching detail views can add value to a data analyst’s user experience. Programming in this kind of interaction automates the creation of complementary charts and increases ease of exploration by linking varied views of the data in a logical way. This tutorial offers a quick example of
AnalyticsCodeData ScienceJavaScriptRR ShinyTutorials

Analytics at Scale: h2o, Apache Spark and R on AWS EMR

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Mark Stephenson
Thursday, 21 June 2018 / Published in Analytics, Data Science, Machine Learning, Predictive Analytics, R, Tutorials
At Red Oak Strategic, we utilize a number of machine learning, AI and predictive analytics libraries, but one of our favorites is h2o.  Not only is it open-source, powerful and scalable, but there is a great community of fellow h2o users that have helped over the years, not to mention the staff leadership at the
Apache SparkCodeData Scienceh2oPredictive AnalyticsRSparkling WaterTutorials

Time Series Forecasting with Machine Learning: An example from Kaggle

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Matt Brown
Monday, 07 May 2018 / Published in Analytics, Code, Data, Data Science, Forecasting, Machine Learning, Predictive Analytics, R, Tutorials
Introduction This post will demonstrate how to use machine learning to forecast time series data. The data set is from a recent Kaggle competition to predict retail sales.       You will learn how to: Build a machine learning model to forecast time series data (data cleansing, feature engineering and modeling) Perform feature engineering to build
CodeData ScienceForecastingPredictive AnalyticsRTime SeriesTutorials

Exploratory Data Analysis of the CDC’s ‘500 Cities Project’ – Part 2

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Matt Brown
Wednesday, 28 March 2018 / Published in Analytics, Code, Data, Data Science, Data Visualizations, R, R-Shiny, Uncategorized
Introduction In Part 1, we built an application to geographically explore the 500 Cities Project dataset from the CDC. In this post, we will demonstrate other exploratory data analysis (EDA) techniques for exploring a new dataset. The analysis will be done with R packages data.table, ggplot2 and highcharter. In this post, you will learn how
CodeDataData ScienceData VisualizationExploratory Data ScienceRR Shiny

Data Processing with RegEx in Python 3

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Daina Andries
Wednesday, 31 January 2018 / Published in Analytics, Code, Data, Data Science, Databases, Python, Tutorials
Applying Regular Expressions This is a tutorial on processing data with regular expressions using Python. It is also a reflection on the advantages and trade-offs that come into play when you use regular expressions. Once you have identified and defined a set of patterns, you can strategically search and extract data from raw text according
CodeData ProcessingData SciencePythonPython 3RegExTutorial

Exploratory Data Analysis of the CDC’s ‘500 Cities Project’ – Part 1

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Matt Brown
Friday, 05 January 2018 / Published in Analytics, Code, Data, Data Science, Data Visualizations, R, R-Shiny
Exploratory data analysis (EDA) is generally the first step in any data science project with the goal being to summarize the main features of the dataset. It helps the analyst gain a better understanding of the available data and often can unearth powerful insights. Data visualization is the most common technique in EDA. During this
CodeData ScienceData VisualizationRR Shiny

Selecting Multiple Locations on a Leaflet Map in R Shiny

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Daina Andries
Thursday, 07 December 2017 / Published in Analytics, Code, Data, Data Science, Data Visualizations, R, R-Shiny, Tutorials
Our team recently designed a dashboard using R Shiny Leaflet allowing users to select many locations at one go on an interactive map. We created the map using the package [crayon-60724806c9f7c870736829-i/], which enables users to draw shapes on R Shiny Leaflet maps. When combined with the package [crayon-60724806c9f82924645589-i/] and a function called [crayon-60724806c9f85242455272-i/], the [crayon-60724806c9f87464346360-i/]  drawing tool can
AnalyticsCodeData ScienceMapsRR ShinyTutorials

How Our Poll Got It Right

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Patrick Stewart
Thursday, 17 November 2016 / Published in Analytics, Data, Political Analytics
This year, the Red Oak Strategic team decided to undertake a new challenge in the world of polling and analytics : conduct a bi-weekly, public, national survey that we would execute and release using the Google Surveys platform. Beginning in August and continuing through the final week of the 2016 election, our partnership with GCS led
2016 ElectionData SciencePoliticsPolling

Could Google and Xbox solve all of polling’s problems?

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Mark Stephenson
Friday, 26 August 2016 / Published in Analytics, Data, Political Analytics, Predictive Analytics
Political polling faces a crisis of confidence. Major news outlets repeatedly ask “What’s the matter with polling?” after major misses like the Bernie Sanders’s primary upset in Michigan, where he beat Hillary Clinton 50–48 despite the fact that she was leading by up to 20 points in reputable polls. There is, however, hope for a
2016 ElectionData SciencePoliticsPolling

Uber & Lyft: Using campaign data science to succeed

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Mark Stephenson
Wednesday, 11 May 2016 / Published in Analytics, Data, Political Analytics, Predictive Analytics
Last Saturday, in what has now been widely publicized and discussed, Uber and Lyft lost an effort, Proposition 1, that would have rolled back a number of regulations on their services. As a result, in one of America’s most forward-thinking tech centers, the services stopped operating almost immediately. Andrew Watts wrote a great analytical piece
Data SciencePoliticsUber
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  • Customizing Click Events: How to Capture and Store Data from JavaScript Objects in R Variables

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  • Analytics at Scale: h2o, Apache Spark and R on AWS EMR

    At Red Oak Strategic, we utilize a number of ma...
  • Time Series Forecasting with Machine Learning: An example from Kaggle

    Introduction This post will demonstrate how to ...

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