3073 search results for "map"

Interactive Maps for John Snow’s Cholera Data

March 28, 2015
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Interactive Maps for John Snow’s Cholera Data

This week, in Istanbul, for the second training on data science, we’ve been discussing classification and regression models, but also visualisation. Including maps. And we did have a brief introduction to the  leaflet package, devtools::install_github("rstudio/leaflet") require(leaflet) To see what can be done with that package, we will use one more time the John Snow’s cholera dataset, discussed in previous...

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Simple Lower US 48 Albers Maps & Local (no-API) City/State Geocoding in R

March 15, 2015
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Simple Lower US 48 Albers Maps & Local (no-API) City/State Geocoding in R

I’ve been seeing an uptick in static US “lower 48″ maps with “meh” projections this year, possibly caused by a flood of new folks resolving to learn R but using pretty old documentation or tutorials. I’ve also been seeing an uptick in folks needing to geocode US city/state to lat/lon. I thought I’d tackle both

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Extracting Heatmap

March 11, 2015
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Inspired by this tweet, I wanted to try to do something similar in JavaScript. Very cool hack: Extracting the original data from a heatmap image with R vector ops #rstats http://t.co/Lbi6FCXdrI pic.twitter.com/LCabkMGjXY— Gregory Piatetsky (@kdnugge...

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NYC Motor Vehicle Collisions – Street-Level Heat Map

March 10, 2015
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NYC Motor Vehicle Collisions – Street-Level Heat Map

In this post I will extend a previous analysis creating a borough-level heat map of NYC motor vehicle collisions. The data is from NYC Open Data. In particular, I will go from borough-level to street-level collisions. The processing of the code is very similar to the previous analysis, with a few more functions that map streets to colors. … Continue reading...

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NYC Motor Vehicle Collisions – Street-Level Heat Map

March 10, 2015
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NYC Motor Vehicle Collisions – Street-Level Heat Map

In this post I will extend a previous analysis creating a borough-level heat map of NYC motor vehicle collisions. The data is from NYC Open Data. In particular, I will go from borough-level to street-level collisions. The processing of the code is very similar to the previous analysis, with a few more functions that map streets to colors. … Continue reading...

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Irrigation area treemaps

March 4, 2015
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Irrigation area treemaps

These visualizations were performed for FAO AQUASTAT. These treemap charts allow for hierarchical organization of information of different types. In the image above, for example, the irrigation areas for each country are represented as the big boxes, within which the technology utilization is displayed in different colors. This allows users …

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Animated great circles 1: flat map to 3D Earth

March 4, 2015
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Animated great circles 1: flat map to 3D Earth

More fun with great circle arcs. Who doesn’t love a good great circles graphic? This time, however, it is an animation. Using R, not only have I animated path traversal along great circle arcs, but I’ve also projected them onto a three dimensional global surface. It was not without its challenges. And yes, the title

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Extracting the original data from a heatmap image

March 4, 2015
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Extracting the original data from a heatmap image

The paper Analysis of the Linux Kernel Evolution Using Code Clone Coverage analysed 136 versions of Linux (from 1.0 to 2.6.18.3) and calculated the amount of source code that was shared, going forward, between each pair of these versions. When I saw the heatmap at the end of the paper (see below) I knew it

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Mapping Paris bikes stands

March 3, 2015
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Mapping Paris bikes stands

A Sharp Sight Labs reader (and now student), Jason P. recently started learning data science. He has a background in data analysis (primarily with Excel and related tools in the Microsoft ecosystem) but he wanted to start learning some of the harder skills of data science. He contacted me after he had diligently reviewed past The post

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John Snow, and Google Maps

February 27, 2015
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John Snow, and Google Maps

In my previous post, I discussed how to use OpenStreetMaps (and standard plotting functions of R) to visualize John Snow’s dataset. But it is also possible to use Google Maps (and ggplot2 types of graphs). library(ggmap) get_london <- get_map(c(-.137,51.513), zoom=17) london <- ggmap(get_london) Again, the tricky part comes from the fact that the coordinate representation system, here, is not...

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