R-Lab #1: hands on R code! | Milan, March 14th

March 1, 2017
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R-Lab #1: hands on R code! | Milan, March 14th

Great news for the MilanoR community: we are launching R-Lab, a monthly R project of co-working with R on real data science projects. Either if you are an R expert, a beginner, or you just curious, you are welcome to join us! The first event will be on March 14th, in Mikamai, Milano. We will introduce the R-Lab project and...

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Sentiment Analysis of The Lord Of The Rings with tidytext

March 1, 2017
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Sentiment Analysis of The Lord Of The Rings with tidytext

You got me thinking about Watson and its unprecedented flexibility in analyzing different data sources (at least according to IBM). So how difficult it would be to analyse sentiment of one of my favorites books using R? Pretty easy actually - all thanks to new package tidytext by Julia Silge and David Robinson… The tidy text format Tidy text format is...

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R Quick tip: Microsoft Cognitive Services’ Text Analytics API

March 1, 2017
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R Quick tip: Microsoft Cognitive Services’ Text Analytics API

Today in class, I taught some fundamentals of API consumption in R. As it was aligned to some Microsoft content, we first used HaveIBeenPwned.com‘s API and then played with Microsoft Cognitive Services‘ Text Analytics API. This brief post overviews what you need to get started, and how you can chain consecutive calls to these APIs …

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ccafs – client for CCAFS General Circulation Models data

March 1, 2017
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ccafs – client for CCAFS General Circulation Models data

I've recently released the new package ccafs, which provides access to data from Climate Change, Agriculture and Food Security (CCAFS; http://ccafs-climate.org/) General Circulation Models (GCM) data. GCM's are a particular type of climate model, used for weather forecasting, and climate change forecasting - read more at https://en.wikipedia.org/wiki/General_circulation_model. ccafs falls in the data client camp - its focus is on getting users data -...

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The R Formula Method: The Bad Parts

February 28, 2017
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The R Formula Method: The Bad Parts

R’s model formula infrastructure was discussed in my previous post. Despite the elegance and convenience of the formula method, there are some aspects that are limiting. Limitations to Extensibility The model formula interface does have some limitations: It can be kludgy with many operations on many variables (e.g., log transforming 50 variables via a formula without using paste) The predvars...

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Copying tables from R to Outlook

February 28, 2017
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Copying tables from R to Outlook

I work in an ecosystem that uses Outlook for e-mail. When I have to communicate results with collaborators one of the most frequent tasks I face is to take a tabular output in R (either a summary table or some sort of tabular output) and send it to collaborators in Outlook. One method is certainly

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testing R code [book review]

February 28, 2017
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testing R code [book review]

When I saw this title among the CRC Press novelties, I immediately ordered it as I though it fairly exciting. Now that I have gone through the book, the excitement has died. Maybe faster than need be as I read it while being stuck in a soulless Schipol airport and missing the only ice-climbing opportunity

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US Babyname Collisions 1880-2014

February 28, 2017
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US Babyname Collisions 1880-2014

Abstract We use US Social Security Administration data to compute the probability of a name clash in a class of year-YYYY born kids during the years 1880-2014. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The markdown+Rknitr source code of this blog is available under a

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A (much belated) update to plotting Kaplan-Meier curves in the tidyverse

February 28, 2017
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A (much belated) update to plotting Kaplan-Meier curves in the tidyverse

One of the most popular posts on this blog has been my attempt to create Kaplan-Meier plots with an aligned table of persons-at-risk below it under the ggplot paradigm. That post was last updated 3 years ago. In the interim, Chris Dardis has built upon these attempts to create a much more stable and feature-rich

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Forecasting gentrification in city neighborhoods, with R

February 28, 2017
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Forecasting gentrification in city neighborhoods, with R

If you've lived in a big city, you're likely familiar with the impact of gentrification. For longtime residents of a neighbourhood, it can represent a decline in the culture and vibrancy of your community; for recent or prospective residents, it can represent a financial opportunity in rising home prices. For those that live in a gentrifying neighbourhood, it's one...

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How to create correlation network plots with corrr and ggraph (and which countries drink like Australia)

February 28, 2017
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How to create correlation network plots with corrr and ggraph (and which countries drink like Australia)

@drsimonj here to show you how to use ggraph and corrr to create correlation network plots like these:  ggraph and corrr The ggraph package by Thomas Lin Pedersen, has just been published on CRAN and it’s so hot right now! What does it do? “ggraph is an extension of ggplot2...

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forecast 8.0

February 28, 2017
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forecast 8.0

In what is now a roughly annual event, the forecast package has been updated on CRAN with a new version, this time 8.0. A few of the more important new features are described below. Check residuals A common task when building forecasting models is to check that the residuals satisfy some assumptions (that they are

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How to annotate a plot in ggplot2

February 28, 2017
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How to annotate a plot in ggplot2

After you master the basics of R and ggplot2, you need to learn the little details. A great example of this is plot annotation. Adding little details like plot annotations help you communicate more clearly and "tell a story" with your plots. The post How to annotate a plot in ggplot2 appeared first on SHARP SIGHT LABS.

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A glance at R-bloggers Twitter feed

February 27, 2017
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A glance at R-bloggers Twitter feed

It’s the second time I write a post about the blog aggregator R-bloggers, probably because I’m all about R blogs now that I have one. My husband says my posts are so meta. My first post was about R blogs names, in this one I shall focus on the last...

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A glance at R-bloggers Twitter feed

February 27, 2017
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A glance at R-bloggers Twitter feed

It’s the second time I write a post about the blog aggregator R-bloggers, probably because I’m all about R blogs now that I have one. My husband says my posts are so meta. My first post was about R blogs names, in this one I shall focus on the last...

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Make your R simulation models 20 times faster

February 27, 2017
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Make your R simulation models  20 times faster

Make your R simulation models 20 times faster R can be frustratingly slow if you use its loops. However, you can speed it up significantly (e.g. 20 times!) using the Rcpp package. That could turn a day long simulation into an hour long simulation. I ...

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ggedit 0.1.1: Shiny module to interactvely edit ggplots within Shiny applications

February 27, 2017
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ggedit is a package that lets users interactively edit ggplot layer and theme aesthetics. In a previous post we showed you how to use it in a collaborative workflow using standard R scripts. More importantly, we highlighted that ggedit outputs to the user, after editing, updated: gg plots, layers, scales and themes as both self-contained … Continue...

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ggraph: ggplot for graphs

February 27, 2017
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ggraph: ggplot for graphs

A graph, a collection of nodes connected by edges, is just data. Whether it's a social network (where nodes are people, and edges are friend relationships), or a decision tree (where nodes are branch criteria or values, and edges decisions), the nature of the graph is easily represented in a data object. It might be represented as a matrix...

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Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart

February 27, 2017
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Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart

Last week, I introduced how to run machine learning applications on Spark from within R, using the sparklyr package. This week, I am showing how to build feed-forward deep neural networks or multilayer perceptrons. The models in this example are built ...

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RSurvey

February 27, 2017
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RSurvey

Early in my science career I believed that any good piece of software included a graphical user interface (GUI). That was many years ago, and during that time I delved deep into the art of Tcl/Tk programming; using the tcltk package to create GUI’s ...

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Reinforcement Learning in R

February 27, 2017
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Reinforcement learning has gained considerable traction as it mines real experiences with the help of trial-and-error learning to model decision-making. Thus, this approach attempts to imitate the fundamental method used by humans of learning optimal behavior without the requirement of an explicit model of the environment. In contrast to many other approaches from the domain … Continue...

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Announcing community R workshops

February 27, 2017
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A big part of why I’ve launched Locke Data is so that I can give back more to my communities. I want to give more time and more support to others. One of the first steps is doing some activities that give financial support to community groups without damaging my startup cashflow! Community R workshops …

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Live Presentation: My Talk at the CDC

February 27, 2017
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Live Presentation: My Talk at the CDC

Last Thursday I had the honor of giving a talk about my open source work to the CDC’s R Users Group. A big thank you... The post Live Presentation: My Talk at the CDC appeared first on AriLamstein.com.

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Tree-based univariate testing

February 26, 2017
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Tree-based univariate testing

When building a predictive model it is a good idea to do a univariate analysis, before throwing the whole bunch in a complex algorithm. This way we get a feel for the potential contribution of each predictor. When a lot of predictors are available one can often make a first selection and only use predictors that show univariate predictive...

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Video Introduction to Bayesian Data Analysis, Part 2: Why use Bayes?

February 26, 2017
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Video Introduction to Bayesian Data Analysis, Part 2: Why use Bayes?

This is video two of a three part introduction to Bayesian data analysis aimed at you who isn’t necessarily that well-versed in probability theory but that do know a little bit of programming. If you haven’t watched part one yet, I really recomme...

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Iteration and closures in R

February 26, 2017
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Iteration and closures in R

I recently read an interesting thread on unexpected behavior in R when creating a list of functions in a loop or iteration. The issue is solved, but I am going to take the liberty to try and re-state and slow down the discussion of the problem (and fix) for clarity. The issue is: are references … Continue...

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Analysis of International T20 matches with yorkr templates

February 25, 2017
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Analysis of International T20 matches with yorkr templates

Introduction In this post I create yorkr templates for International T20 matches that are available on Cricsheet. With these templates you can convert all T20 data which is in yaml format to R dataframes. Further I create data and the necessary templates for analyzing. All of these templates can be accessed from Github at yorkrT20Template. The … Continue...

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Logistic Regression Regularized with Optimization

February 25, 2017
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Logistic Regression Regularized with Optimization

Logistic regression predicts the probability of the outcome being true. In this exercise, we will implement a logistic regression and apply it to two different data sets. The file ex2data1.txt contains the dataset for the first part of the exercise and ex2data2.txt is data that we will use in the second part of the exercise. Related Post

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Success rates of appeals to the Supreme Court by Circuit

February 25, 2017
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Success rates of appeals to the Supreme Court by Circuit

In the chaos of the last month or so of United States of America governance, one item that grabbed my attention was the claim by President Trump that 80% of appeals decided by the Ninth Circuit Court of Appeal are overturned by the Supreme Court of the...

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