Introducing the VisualResume (v0.1.0) R Package

January 2, 2017
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Introducing the VisualResume (v0.1.0) R Package

Visual Resumes are cool Some years ago, during the course of one of my regular Google image searches for inspiring designs, I discovered Visual Resumes (aka. Infographic Resumes) like this one from Michael Anderson. I immediately fell in love. And of course, I quickly set out to create my own in R. The result is a new package called VisualResume....

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Understanding mixture models and expectation-maximization (using baseball statistics)

January 2, 2017
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Understanding mixture models and expectation-maximization (using baseball statistics)

Previously in this series: Understanding the beta distribution Understanding empirical Bayes estimation Understanding credible intervals Understanding the Bayesian approach to false discovery rates Understanding Bayesian A/B testing Understanding beta binomial regression Understanding empirical Bayesian hierarchical modeling In this series on empirical Bayesian methods on baseball data, we’ve been...

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Django and R on Heroku

January 2, 2017
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I’ve been playing with Django for a while now and I’m loving it. Don’t get me wrong, I still love Shiny, but Django is pretty tough to beat for data-heavy projects and managing user sessions. For deployment, I’ve been using Heroku and am very h...

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Handling Class Imbalance with R and Caret – Caveats when using the AUC

January 2, 2017
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Handling Class Imbalance with R and Caret – Caveats when using the AUC

In my last post, I went over how weighting and sampling methods can help to improve predictive performance in the case of imbalanced classes. I also included an applied example with a simulated dataset that used the area under the ROC curve (AUC) as th...

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(lazy)Loading Cached Chunks into an Interactive R Session

January 2, 2017
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If you cache code chunks when using knitr to generate reproducible documents then you’ve likely had the issue arrise of needing to load the results of cached chunks into an active interactive R session. The functions lazyload_cache_dir and lazyload_...

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Removing Personal Bias From Flu Severity Estimation (a.k.a. Misery Loves Data)

January 2, 2017
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Removing Personal Bias From Flu Severity Estimation (a.k.a. Misery Loves Data)

The family got hit pretty hard with the flu right as the Christmas festivities started and we were all pretty much bed-ridden zombies up until today (2017-01-02). When in the throes of a very bad ILI it’s easy to imagine that you’re a victim of a severe outbreak, especially with ancillary data from others that... Continue reading...

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May the Force of R be With You, Always!

January 2, 2017
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May the Force of R be With You, Always!

With my Telegram account connected to @TeleR, the force of R can always be with me, where I have data. The following is a screenshot of my mobile: If you want to have R where you are too, you will only need a Telegram account, then search for the pu...

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Shiny Chart Builder – Explore your database with a point-and-click interface

January 2, 2017
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Shiny Chart Builder – Explore your database with a point-and-click interface

You can use R's Shiny to create an interactive dashboard with this application, make your database explorable without knowing SQL or R!

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eoda celebrates R – don’t miss the date and win!

January 2, 2017
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eoda celebrates R – don’t miss the date and win!

#Rstatsgoes10k: Join eoda in the celebration of R and take the chance to win with your prediction! The easiest way to stay up-to-date regarding the current number of R packages is to follow eoda’s automated Twitter bot @Rstatsgoes10k. This bot regularly informs its followers of the status quo so that participants of the contest will …

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Animations in R using Plotly

January 2, 2017
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Animations in R using Plotly

Like last year, lets have some fun with the Plotly package. We’ll try out Plotly’s new animation capabilities. You should now have something like this: For mode details visit: Plotly for R by Carson Seivert.

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Distributional Semantics in R: Part 2 Entity Recognition w. {openNLP}

January 2, 2017
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Distributional Semantics in R: Part 2 Entity Recognition w. {openNLP}

The R code for this tutorial on Methods of Distributional Semantics in R is found in the respective GitHub repository. You will find .R, .Rmd, and .html files corresponding to each part of this tutorial (e.g. DistSemanticsBelgradeR-Part2.R, DistSemant...

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Forcasting Natural Catastrophes (is rather difficult)

January 2, 2017
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Forcasting Natural Catastrophes (is rather difficult)

Following my previous post, I wanted to spend more time, on the time series with “global weather-related disaster losses as a proportion of global GDP” over the time period 1990-2016 that Roger Pilke sent me last night. db=data.frame(year=1990:2016, ratio=c(.23,.27,.32,.37,.22,.26,.29,.15,.40,.28,.14,.09,.24,.18,.29,.51,.13,.17,.25,.13,.21,.29,.25,.2,.15,.12,.12)) In my previous post, I spend some time explaining that we should provide some sort of ‘confidence interval’ when we...

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How to download and organize financial data from yahoo finance for several tickers

January 2, 2017
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How to download and organize financial data from yahoo finance for several tickers

Using package BatchGetSymbols - One of the great things of working in finance is that financial datasets are freely available from sources such as Google and Yahoo Finance. This is an excelent feature for building up to date conte...

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Script to convert numeric integer data of data frame column into a digit matrix.

January 1, 2017
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Script to convert numeric integer data of data frame column into a digit matrix.

At some point I found the need to manipulate and analyze each digit of a series of integer values, perform statistics with each of them and in some occasions add zeros at the beginning of each number. So I gave...

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What is a Linear Trend, by the way?

January 1, 2017
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What is a Linear Trend, by the way?

I had a very stranger discussion on twitter (yes, another one), about regression curves. I think it started with a tweet based on some xkcd picture (just for fun, because it was New Year’s Day) “don’t trust linear regressions” https://t.co/exUCvyRd1G pic.twitter.com/O6rBJfkULa — Arthur Charpentier (@freakonometrics) 1 janvier 2017 There were comments on that picture, by econometricians, mainly about ‘significant’...

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Welcome to Data R Value

January 1, 2017
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Welcome to Data R Value

HelloThank you very much for reading this blog that will be dedicated to everything related to the R programming language and to data science field. I will be publishing scripts, hints, algorithms and many more things. I will also be publishing data...

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3PL models viewed through the lens of total probability theorem

January 1, 2017
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3PL models viewed through the lens of total probability theorem

As I currently am the NPM for PISA in Colombia, I must assist to several meetings dealing with the proper implementation of this assessment in my country. Few of them are devoted to the analysis of this kind of data (coming from IRT models). As usual, ...

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Dan Thompson 2017-01-29 11:29:11

January 1, 2017
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Summary In this blog post I will show you how to make your own personal assistant (think Siri, Cortana, Alexa) in R, very quickly. This will be done in three steps: Get R to recognise your voice and convert it to text Set up a system which us...

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Building Shiny App exercises part 4

January 1, 2017
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Building Shiny App exercises part 4

APPLICATION LAYOUT & REACTIVITY The fourth part of our series is “separated” into two “sub-parts”. In the first one we will start building the skeleton of our application by using tabsetPanel. This is how we will separate the sections of our app and also organize its structure better. In the second part you will learn

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How to perform PCA on R

January 1, 2017
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How to perform PCA on R

This is a practical tutorial on performing PCA on R. If you would like to understand how PCA works, please see my plain English explainer here. Reminder: Principal Component Analysis (PCA) is a method used to reduce the number of variables in a dataset. We are using R’s USArrests dataset, a dataset from 1973 showing,

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My first post!

January 1, 2017
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My first post!

A little bit about me and this blog - Hello everyone! This is the first (ever) post for a new blog about Finance and R. My name is Marcelo Perlin and my day job is assistant professor of Finance in Federal...

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convert graphic object to tree object using treeio

January 1, 2017
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convert graphic object to tree object using treeio

I have splitted ggtree to 2 packages, treeio and ggtree. Now ggtree is mainly focus on visualization and annotation, while treeio focus on parsing and exporting tree files. Here is a welcome message from treeio that you can convert ggtree output to tree object which can be exported as newick or nexus file if you want. Thanks to ggplot2, output...

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A Theory of Nested Cross Simulation

January 1, 2017
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A Theory of Nested Cross Simulation

[Reader’s Note. Some of our articles are applied and some of our articles are more theoretical. The following article is more theoretical, and requires fairly formal notation to even work through. However, it should be of interest as it touches on some of the fine points of cross-validation that are quite hard to perceive or … Continue...

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tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

December 31, 2016
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tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

My new package, tidyquant, is now available on CRAN. tidyquant integrates the best quantitative resources for collecting and analyzing quantitative data, xts, quantmod and TTR, with the tidy data infrastructure of the tidyverse allowing for seamless in...

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Our R package roundup

December 31, 2016
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Our R package roundup

A year in review And yet again, it’s that time of the year when one eats too much and gets in a reflective mood! 2016 is nearly over, and us bloggers here at opiateforthemass.es thought it would be nice to argue endlessly which R package was th...

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Turning KML into tidy data frames

Turning KML into tidy data frames

This note briefly introduces the tidykml package, which turns basic KML geometries into tidy data frames that can be visualized with ggplot2. Summary The tidykml package provides a quick way to import data from Google My Maps into R, in a format that makes it easy to manipulate the data and visualize it with ggplot2. Below is...

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Power BI custom visuals, based on R

December 30, 2016
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Power BI custom visuals, based on R

You've been able to include user-defined charts using R in Power BI dashboards for a while now, but a recent update to Power BI includes seven new custom charts based on R in the customs visuals gallery. You can see the new chart types by visiting the Power BI Custom Visuals Gallery and clicking on the "R-powered visuals" tab....

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Fireworks (in R)

December 30, 2016
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Fireworks (in R)

New Year – a new chapter, new verse, or just the same old story ? Ultimately we write it. The choice is ours. ― Alex Morritt The Analytics Lab and Cmotions wish everybody a happy year. A year full of challenges, new experiences and new knowledge. Github library(ggplot2) rm(list = ls()) # First rocket t1

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Outlier App: An Interactive Visualization of Outlier Algorithms

December 30, 2016
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Outlier App: An Interactive Visualization of Outlier Algorithms

I was recently trying various outlier detection algorithms. For me, the best way to understand an algorithm is to tinker with it. I built a shiny app that allows you to play around with various outlier algorithms and wanted to share it with everyone. The shiny app is available on my site, but even better, Related Post

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