Series
- Using R (21)
- Using WordPress (3)
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Recent Posts
- Improved Python-style Logging in R
- Introducing the PWFSLSmoke Package
- Python-style Logging in R
- When k-means Clustering Fails
- Visualizing Bikeshare Data
- Function Argument Lists and missing()
- MazamaSpatialUtils — Ebola Map Example
- Installing subversion 1.7.10 on OSX Yosemite
- MazamaSpatialUtils Package
- R Class for Wildfire Scientists
Blogroll
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Category Archives: Data Visualization
Visualizing Bikeshare Data
This entry is part 18 of 21 in the series Using RSeattle’s Pronto bikeshare system recently announced a Data Challenge for data visualization using their first year of trip data. As avid cyclists and data analysis junkies, we of course took … read more …
MazamaSpatialUtils — Ebola Map Example
This entry is part 16 of 21 in the series Using R The MazamaSpatialUtils package on CRAN has just been updated with additional shape file conversion scripts and location buffering so that points located just outside of polygons (i.e. coastal … read more …
R Class for Wildfire Scientists
This entry is part 14 of 21 in the series Using RMazama Science has just finished creating class materials on using R for the AirFire team at the USFS Pacific Wildland Fire Sciences Lab in Seattle, Washington. This team of … read more …
Posted in Data Management, Data Visualization, R
Tagged AirFire, BlueSky, forest, netcdf, R, smoke, USFS, wildfire
3 Comments
Population Databrowser
This entry is part 13 of 21 in the series Using RAt Mazama Science we produce web based tools for interrogating important datasets. We are proud to announce the release of a new Population databrowser that allows users to review … read more …
Posted in Data Visualization, R, User Interface Design
Tagged FIPS, i18n, ISO, population, R
Comments Off on Population Databrowser
Using R — Working with Geospatial Data (and ggplot2)
This is a follow-up blog-post to an earlier introductory post by Steven Brey: Using R: Working with Geospatial Data. In this post, we’ll learn how to plot geospatial data in ggplot2. Why might we want to do this? Well, it’s really … read more …