2618 search results for "ggplot2"

Points, Polygons and Power Outages

December 27, 2013
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Points, Polygons and Power Outages

Most of my free coding time has been spent tweaking a D3-based live power outage tracker for Central Maine Power customers (there’s also a woefully less-featured Shiny app for it, too). There is some R associated with the D3 vis, but it’s limited to a cron job that’s makes the CSV files for the sparklines

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Coxcomb plots and ‘spiecharts’ in R

December 27, 2013
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Coxcomb plots and ‘spiecharts’ in R

I was contacted recently by a housing organisation who wanted an attractive visualisation of their finances, arranged in a circular form. Because there were two 4 continuous variables to include, all of which were proportions of each other, the client suggested a plot similar to a pie chart, but with each segment extending out a different radius from the segment. I realised...

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Sentence Drawing: Part II

December 23, 2013
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Sentence Drawing: Part II

In a recent blog post I introduced Stefanie Posavec‘s Sentence Drawings. We created this ggplot2 rendition: We left off weighing the aesthetics of the Sentence Drawing with information of quality visualizations. I asked others to think of ways to display … Continue reading →

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24 Days of R: Day 23

December 23, 2013
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24 Days of R: Day 23

Penultimate post, I'm going to take a quick look at the Gini indicator for wealth inequality. Data comes from the World Bank. I've downloaded the zipped file, decompressed it and given it a different name. I'm going to This will give us a decent set of data. How does this look when we plot it?

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How much faster is calibration with parallel processing and/or R byte-code compiling ?

December 20, 2013
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How much faster is calibration with parallel processing and/or R byte-code compiling ?

The Svensson model is a 6-factor yield curve model that has been derived from the Nelson-Siegel model in : Svensson, L. E. (1995). Estimating forward interest rates with the extended Nelson & Siegel method. Sveriges Riksbank Quarterly Review, 3(1) :13-26. … Continue reading →

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24 Days of R: Day 19

December 19, 2013
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24 Days of R: Day 19

Carrying on with the multi-level model, I'm going to look at the paid and incurred workers comp losses for a large number of insurance companies. This is a similar exercise to what I did last night, but I'm now working with real, rather than simulated data and the stochastic process is assumed to be different.

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The distribution of Twitter follower counts

December 18, 2013
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The distribution of Twitter follower counts

My Twitter account @revodavid has, of this writing, 8828 followers. But is that below or above average amongst active Twitter accounts? Since Twitter doesn't publish statistics of follower counts, I've really had little idea. Until now, that is, because Jon Bruner has done some independent research to estimate the distribution of number of followers amongst active Twitter users. Bruner...

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Twelve Days 2013: Sensor Fusion

December 18, 2013
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Twelve Days 2013: Sensor Fusion

Day Seven: Sensor Fusion TL/DR Sensor fusion is a generic term for techniques that address the issue of combining multiple noisy estimates of state in an optimal fashion. There’s a straight forward view of it as the gain on a Kalman–Bucy filter, and an even simpler interpretation under the central limit theorem. A Primer on Stochastic Control Control theory is...

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Book Review: Analyzing Baseball Data with R

December 17, 2013
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Book Review: Analyzing Baseball Data with R

by Max Marchi and Jim Albert (2014, CRC Press)The Sabermetric bookshelf, #3Here we have the perfect book for anyone who stumbles across this blog--the intersection of R and baseball data. The open source statistical programming environment of R is a gr...

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Cluster Analysis using R

December 17, 2013
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Cluster Analysis using R

In this post, I will explain you about Cluster Analysis, The process of grouping objects/individuals together in such a way that objects/individuals in one group are more similar than objects/individuals in other groups. For example, from a ticket booking engine database identifying clients with similar booking activities and group them together (called Clusters). Later these identified clusters can be...

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