July 2016

Networks, mazes, and R (Rmaze)

July 20, 2016 | Vessy

Like many people who work with networks (aka graphs), I like to emphasize their usability and applicability to different problems. If some phenomena can be described by its objects and relationships among those objects – well, hello networks. One of … Continue reading → [Read more...]

An analysis of Pokémon Go types, created with R

July 20, 2016 | David Smith

As anyone who has tried Pokémon Go recently is probably aware, Pokémon come in different types. A Pokémon's type affects where and when it appears, and the types of attacks it is vulnerable to. Some types, like Normal, Water and Grass are common; others, like Fairy and ... [Read more...]

Life Expectancy by Country

July 20, 2016 | Andrew Collier

I was rather inspired by this plot on Wikipedia’s List of Countries by Life Expectancy. Shouldn’t be too hard to reproduce with a bit of scraping. Here are the results (click on the static image to view the interactive plot): The bubble plot above compares female and male ... [Read more...]

Giving back with code

July 20, 2016 | Steph

From code in answers on Stack Overflow to R packages or full programs, there’s a lot of code being written and given away. This post examines some of the reasons why the people writing all that code do it, why you should consider giving back with code, and how ...
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leading edge analysis

July 20, 2016 | R on Guangchuang Yu

leading edge and core enrichment Leading edge analysis reports Tags to indicate the percentage of genes contributing to the enrichment score, List to indicate where in the list the enrichment score is attained and Signal for enrichment signal strength. It would also be very interesting to get the core enriched ...
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Random Forests in R

July 19, 2016 | R on The Stats Guy

Introduction As the name suggests, random forest models basically contain an ensemble of decision tree models, with each decision tree predicting the same response variable. The response may be categorical, in which case being a classification prob...
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Calculating Memory Requirements

July 19, 2016 | Daniel's Blog

I had a conversation with people at the office about size and memory requirements that a computer must have to deal with a data frame. It started like this: suppose you have a data frame with 2,000,000 rows and 250 columns, all of which are numeric dat... [Read more...]

Candlestick charts using Quandl and Plotly

July 19, 2016 | Riddhiman

In this post we’ll show how to create candle stick charts using the new plotly 4.0 syntax. You can refer to this older post as well. This time we’ll use the Quandl package to retrieve stock data. See here for more details. [crayon-578e6d0900fb6176475862/] [Read more...]

dplyr and Zika – Epilogue

July 19, 2016 | Stevie P

I really thought I was done with the Express dplyr series though on completion of the second part I received many messages requesting more examples of using dplyr with ggplot along with some other types of information such as the Zika virus data which can be downloaded from Github. These ...
[Read more...]

Principal Component Analysis Cluster Plots with Plotly

July 19, 2016 | Sahir Bhatnagar

The Problem When clustering data using principal component analysis, it is often of interest to visually inspect how well the data points separate in 2-D space based on principal component scores. While this is fairly straightforward to visualize with a scatterplot, the plot can become cluttered quickly with annotations as ... [Read more...]

Rcpp 0.12.6: Rolling on

July 19, 2016 | Thinking inside the box

The sixth update in the 0.12.* series of Rcpp has arrived on the CRAN network for GNU R a few hours ago, and was just pushed to Debian. This 0.12.6 release follows the 0.12.0 release from late July, the 0.12.1 release in September, the 0.12.2 release in November, the 0.12.3 release in January, the 0.12.4 release in ... [Read more...]
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