535 search results for "boxplot"

Body Temperature Series of Two Beavers

December 4, 2015
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Body Temperature Series of Two Beavers

This short post will explore a funny dataset that forms part of R’s dataset library. The dataset will loaded out of interest of its content as well as using it to enagage with Hadley Wickhams’s ggplot2 package. The dataset that will be used to expl...

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Using knitr and R to make instructor/student handout versions

November 29, 2015
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I teach some of my lab sections using R, and so I need to create lab handouts that include nicely formatted R commands and R output as an example for the students. These handouts will also include exercises where the students will be writing their own R code, or interpreting the results, or generating figures.

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What the candidates say, analyzing republican debates using R

November 26, 2015
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What the candidates say, analyzing republican debates using R

As most people realize, this is probably one of the most data-rich primary campaigns in history, with hundreds of professional pollsters poring over every data-point trying to understand voter’s intention. So here is another data-rich post to that end. I was glad to discover the University of California at Santa Barbara’s webpage with tons of high-quality data related to the...

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Modeling gene expression with broom: a case study in tidy analysis

November 25, 2015
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Modeling gene expression with broom: a case study in tidy analysis

Previously in this series Cleaning and visualizing genomic data: a case study in tidy analysis In the last post, we examined an available genomic dataset from Brauer et al 2008 about yeast gene expression under nutrient starvation. We learned to tidy it with the dplyr and tidyr packages, and saw how useful this tidied form is for visualizing...

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How to Search for Census Data from R

November 16, 2015
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How to Search for Census Data from R

In my course Learn to Map Census Data in R I provide people with a handful of interesting demographics to analyze. This is convenient for teaching, but people often want to search for other demographic statistics. To address that, today I will work through an example of starting with a simple demographic question and using R The post

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Web Scraping: The Sequel | Propwall.my

November 13, 2015
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Web Scraping: The Sequel | Propwall.my

Alright. Time to take another shot at web scraping. My attempt at scraping data off iBilik.my left me a little frustrated because of how long it took, and also at how i couldn’t get much information because of all the duplicated … Continue reading →

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Free Webinar: Learn to Map Unemployment Data in R

November 10, 2015
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Free Webinar: Learn to Map Unemployment Data in R

Last month I ran my first webinar (“Make a Census Explorer with Shiny”). About 100 people showed up, and feedback from the participants was great. I also had a lot of fun myself. Because of this, I’ve decided to do one more webinar before my free trial with the webinar service ends. Here are the The post

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Factor codings for models in R

Factor codings for models in R

I am holding an exercise on generalised models these days. Preparing a task on factor coding in generalised linear models, I realised that the help on the internet on that is not so easy to understand. At least what I found. So in order to help people ...

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The 5th Tribe, Support Vector Machines and caret

October 15, 2015
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The 5th Tribe, Support Vector Machines and caret

by Joseph Rickert In his new book, The Master Algorithm, Pedro Domingos takes on the heroic task of explaining machine learning to a wide audience and classifies machine learning practitioners into 5 tribes*, each with its own fundamental approach to learning problems. To the 5th tribe, the analogizers, Pedro ascribes the Support Vector Machine (SVM) as it's master algorithm....

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A high quality plot

October 14, 2015
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A high quality plot

I’ll keep this post short and sweet. Here’s some code to get a really nice looking plot in R. It has a high pixel count to produce a high resolution output that can be used in a word document. Because of this, the size of everything in the plot (axes, points, text, axis labels, etc)

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