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- Using R (22)
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Recent Posts
- Logging and Error Handling in Operational Systems
- PWFSLSmoke 1.0: Visualizing Wildfire Smoke Data
- 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
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Tag Archives: R
Logging and Error Handling in Operational Systems
Operational systems, by definition, need to work without human input. Systems are considered “operational” after they have ben thoroughly tested and shown to work properly with a variety of input. However, no software is perfect and no real-world system operates … read more …
PWFSLSmoke 1.0: Visualizing Wildfire Smoke Data
Mazama Science has released the first official version (1.0) of the PWFSLSmoke R package for working with PM2.5 monitoring data. A beta version was released last year, along with an accompanying blog post. In this post, we discuss the purpose … read more …
Python-style Logging in R
We are increasingly using R in “operational” settings that require robust error handling and logging. In this post we describe a quick-and-dirty way to get python style multi-level log files by wrapping the futile.logger package.
When k-means Clustering Fails
Letting the computer automatically find groupings in data is incredibly powerful and is at the heart of “data mining” and “machine learning”. One of the most widely used methods for clustering data is k-means clustering. Unfortunately, k-means clustering can fail … read more …