2657 search results for "Ggplot2"

Visualizing bivariate shrinkage

January 20, 2015
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Visualizing bivariate shrinkage

Inspired by this post about visualizing shrinkage on Coppelia, and this thread about visualizing mixed models on Stack Exchange, I started thinking about how to visualize shrinkage in more than one dimension. One might find themselves in this situation with a varying slope, varying intercept hierarichical (mixed effects) model, a model with two varying intercepts, etc. Then...

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Simple Data Science Of Global Warming In KDnuggets

January 20, 2015
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Simple Data Science Of Global Warming In KDnuggets

Would love to get a post from you for KDnuggets (Gregory Piatetsky, KDnuggets President) Some days ago, Gregory Piatetsky invited me to write a post for KDnuggets. I couldn’t say no. He suggested to me some topics and I decided to experiment around climate change to demonstrate how easy is to see some evidences of … Continue reading...

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Building a choropleth map of Italy using mapIT

January 19, 2015
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Building a choropleth map of Italy using mapIT

In the R environment, different packages to draw maps a

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How to Predict Where Will Next Disaster Strike?

January 18, 2015
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How to Predict Where Will Next Disaster Strike?

It is amusing coincidence that another MOOC that I took this week (Geospatial Intelligence & the Geospatial revolution) mentioned disasters. About the other course see my recent Disasters: Myth or the Reality post.In Geospatial Intelligence they gave a weird assignment: one need to mark the location on the world map where...

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stacked plot in R

January 18, 2015
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stacked plot in R

Consider the following example: there is a three-stage truck maintenance pipeline. Initially, when a Truck comes to the maintenance service, it is added to the first stage and its status in the pipeline is set to "New". When the technicians start working on it, for diagnosis the problem and removing the issue, its status is changed to "in progress"....

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NASA GISS’s Annual Global Temperature Anomaly Trends (dplyr/ggplot version)

January 18, 2015
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NASA GISS’s Annual Global Temperature Anomaly Trends (dplyr/ggplot version)

D Kelly O’Day did a great post on charting NASA’s Goddard Institute for Space Studies (GISS) temperature anomaly data, but it sticks with base R for data munging & plotting. While there’s absolutely nothing wrong with base R operations, I thought a modern take on the chart using dplyr, magrittr & tidyr for data manipulation

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K-means clustering is not a free lunch

January 15, 2015
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K-means clustering is not a free lunch

I recently came across this question on Cross Validated, and I thought it offered a great opportunity to use R and ggplot2 to explore, in depth, the assumptions underlying the k-means algorithm. The question, and my response, follow. K-means is a widely used method in cluster analysis. In my understanding, this method does NOT require ANY assumptions,...

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Seven 3D Graphs You Can Make In Excel, Python, MATLAB, R, & LaTeX

January 15, 2015
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Seven 3D Graphs You Can Make In Excel, Python, MATLAB, R, & LaTeX

Plotly’s interactive 3D graphs let you make graphs from (click the links for tutorials): our web app, Excel, Google Docs, Python, MATLAB, and R. Click any image below to go to the full-screen interactive version. Also, news for users with on-premise needs. Plotly On-Premise can be hosted on a private server. Contact us...

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Some basics for base graphics

January 15, 2015
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Some basics for base graphics

by Joseph Rickert One of the greatest strengths of the R language is surely the base graphics capabilities. Grid graphics, lattice, ggplot2, bigvis and the many R packages that interface with javascript D3 graphics have added astounding capabilities, well beyond what can be achieved with base graphics alone. Nevertheless, the quick, one line, base graphics plots ( like plot()...

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Using the microbenchmark package to compare the execution time of R expressions

January 14, 2015
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Using the microbenchmark package to compare the execution time of R expressions

I recently learned about the microbenchmark package while browsing through Hadley’s advanced R programming book. I’ve done some quick benchmarking using system.time() in a for loop and taking the average, but the microbenchmark function in the microbenchmark package makes this much easier. Hadley gives the example of taking the square root of a vector using the built-in...

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