Comparing Air Quality Sites

Air quality continues to be in the news with New York Times articles like these:

A quick review of web based air quality resources shows a range of sites featuring maps, time series plots and relevant information.

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Easy Rolling Means with MazamaRollUtils

Our goal in creating a new package of C++ rolling functions is to build up a suite of functions useful in environmental time series analysis. We want these functions to be available in a neutral environment with no underlying data model. The functions are as straightforward to use as is reasonably possible with a target audience of data analysts at any level of R expertise.

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Beautiful Maps with MazamaSpatialPlots

Many of us have become addicted to The NY Times COVID maps — maps of US state or county level data colored by cases, vaccinations, per capita infections, etc. While recreating maps like these in R is possible, it is disappointingly difficult. The just released MazamaSpatialPlots R package takes a first stab at remedying this situation.

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Using R – Calling C code ‘Hello World!’

One of the reasons that R has so much functionality is that people have incorporated a lot of academic code written in C, C++, Fortran and Java into various packages.  Libraries written in these languages are often both robust and fast.  If you are using R to support people in a particular field, you may be called upon to incorporate some outside code into your R environment.  Unfortunately, much of the documentation on how to do this is written at a very high level.  In this post we will distil some of the available information on calling C code from R into three “Hello World” examples.

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Ten UNIX commands every data manager should know

Working with data from varied sources can be frustrating — some data will be in CSV format; some in XML; some available as HTML pages; other data as relational databases or MS Excel spreadsheets.

This post will cover the UNIX tools that every data manager needs to be familiar with in order to work with varied data sources.

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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 with 100% availability or 100% consistent input. Things occasionally go wrong – perhaps intermittently. In a situation with occasional failures it is vitally important to have good logging and error handling. The MazamaCoreUtils R package helps with these tasks.

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