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Mark Needham11/23/14
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R: Refactoring to dplyr

I’ve been looking back over some of the early code I wrote using R before I knew about the dplyr library and thought it’d be an interesting exercise to refactor some of the snippets.

John Walter11/23/14
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The Best of the Week (Nov 14): IoT Zone

Make sure you didn't miss anything with this list of the Best of the Week in the IoT Zone (November 7 - November 14). This week includes a look at the WatchKit SDK, the effect of IoT on our lives, and the role of logging in the IoT.

Erich Styger11/22/14
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Engineering Joke of the Week: The Frog

A little engineering humor for your weekend...

Mark Needham11/22/14
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R: dplyr - Group by field dynamically

A few months ago I wrote a blog explaining how to dynamically/programatically group a data frame by a field using dplyr but that approach has been deprecated in the latest version. It turns out the ‘group_by_’ function doesn’t want to receive a list of fields so let’s remove the call to list:

Michael Sahota11/21/14
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People over Process

Agile and Lean are a means to an end. Once we are clear what our goals are and our approach is consistent with what we truly value, then we may hope for success. We outline a fundamentally different approach for organizational change: one where valuing people is integral to building lasting success.

Allan Kelly11/21/14
3 replies

Does Agile require cultural change?

I sit in Agile conferences and I hear people say “To really become Agile you need culture change.” And I agree with them. But…

Mike Cottmeyer11/21/14
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Replacing Backlog Grooming

Over the last few years, I’ve worked with numerous teams. One thing they all struggle with is backlog grooming. Over the last few years I have evolved my practice of backlog grooming.

Mark Needham11/21/14
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R: Joining multiple data frames

I’ve been looking through the code from Martin Eastwood’s excellent talk ‘Predicting Football Using R‘ and was intrigued by the code which reshaped the data into that expected by glm. I really like dplyr’s pipelining function so I thought I’d try and translate Martin’s code to use that and other dplyr functions.

Rob J Hyndman11/20/14
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Seasonal Periods

The “fre­quency” is the num­ber of obser­va­tions per sea­son. This is the oppo­site of the def­i­n­i­tion of fre­quency in physics, or in Fourier analy­sis, where “period” is the length of the cycle, and “fre­quency” is the inverse of period. When using the ts() func­tion in R, the fol­low­ing choices should be used.

Maneesh Joshi11/20/14
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Top 5 Mobile APM Myths: Myths 1 & 2

There is a lot of confusion in the market today. So in this blog post, I’d like to dispel some key myths around mobile apps. And how, with the right mAPM tool, you can nail your mobile app experience — both interactivity-wise and performance-wise — and thereby win the market.

Rick Delgado11/19/14
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Desktop-as-a-Service and BYOD: Two Growing Complementary Trends

BYOD and DaaS are both growing trends that are making bigger impacts in the business world with each passing year. One of the reasons both are growing at such a steady pace is how they work together so effectively.

Chris Odell11/19/14
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The Single Point Of Failure

As a SOHO (Solo Home Office) Developer one of the many challenges is the fact that there is no one else to discuss code changes with. Without someone to discuss changes with your blind spots will not be covered by a colleague looking at your code, potentially more bugs could creep into your code base and there are less opportunities to learn from other peoples experiences. So what can you do? Well here are some suggestions.

John Cook11/19/14
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People want Swiss Army Knives

I basically agree with the Unix philosophy that tools should do one thing well, but even Unix doesn’t follow this principle strictly in practice. One reason is that “thing” and “well” depend on context. The “thing” that a toolmaker has in mind may not exactly be the “thing” the user has in mind, and the user may have a different idea of when a tool has served well enough.

Ricky Ho11/19/14
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The Common Data Science Project Flow

While working across multiple data science projects, I observed a similar pattern across a group of strategic data science projects where a common methodology can be used. In this post, I want to sketch this methodology at a high level.

Raymond Camden11/18/14
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Syncing Brackets extensions across multiple machines

This really isn't a new tip, but as someone just asked on Twitter for a quick explanation, I thought I'd write it up. If you want to sync Brackets extensions across multiple machines, the easiest way to do it is with Dropbox, or a Dropbox-like service.