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Tracking Coronavirus: Building Parameterized Reports to Analyze Changing Data Sources

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Tyler Sanders
Wednesday, 01 April 2020 / Published in Data Visualizations, JavaScript, R, R-Shiny, Tutorials
The pace of our modern world, and the impressive volume of data we collect on a daily basis, can be dizzying. Take for example, the hour-by-hour updates and colorful dashboards made by news outlets as they track the spread of novel coronavirus (Covid-19). Organizations need quick and consistent solutions for exploring, analyzing, and acting on
CodeData Visualizationggplot2RRShinyTutorials

Draw Rotatable 3D Charts in R Shiny with Highcharts and JQuery

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Daina Andries
Wednesday, 13 March 2019 / Published in Data Visualizations, JavaScript, R, R-Shiny, Tutorials
While it might be tempting to liven up a report or presentation with a few 3D graphs, two-dimensional representation is generally better when numbers are the primary information you want to communicate. Nevertheless, on occasions when numeric values aren’t the primary focus, and you’re more interested in showing the shape of the data, adding a
CodeData VisualizationHighchartsJavaScriptJQueryRRShinyTutorials

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

Blockchain from a Data Science Perspective

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Daina Andries
Thursday, 26 April 2018 / Published in Blockchain, Data, Data Science, Financial Analytics
Imagine someone were to mint a new coin and give it to you. You then buy something and give it to someone else, and so on. Every time this coin changes hands, a record of the transaction is engraved on the coin. Every transaction in the history of that coin’s existence is in plain sight
BlockchainCodeData ProcessingData Science

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

How To: Add and Call Excel Macro from Python Using Pandas, Win32 and PyMySQL

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Mark Stephenson
Thursday, 14 December 2017 / Published in Code, Data, Data Science, Excel, Python, R
Frequently, we encounter projects that require the combined use of Python, Microsoft Excel and some external databases that can only be accessed via Excel, or use cases that require the end product to be output to that format.  Excel is still used as a key program for the vast majority of businesses and we are
CodeData ScienceExcelTutorials
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Recent Posts

  • Tracking Coronavirus: Building Parameterized Reports to Analyze Changing Data Sources

    The pace of our modern world, and the impressiv...
  • Draw Rotatable 3D Charts in R Shiny with Highcharts and JQuery

    While it might be tempting to liven up a report...
  • Customizing Click Events: How to Capture and Store Data from JavaScript Objects in R Variables

    Interaction Design for Data Exploration Visuali...
  • 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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