Closed geanders closed 8 years ago
@geanders thanks for the PR - made a few comments for changes
Thanks so much for taking the time to review. I've made the suggested changes.
thanks @geanders merged
Thank you so much! I really appreciate you taking the time on this pull request.
Would you let me know the next time you submit a version of rnoaa to CRAN? I have a student working on a package that builds on some of these functions, so it will be good to know for getting the dependencies straight in her package code.
Best,
Brooke
From: Scott Chamberlain notifications@github.com Sent: Tuesday, August 23, 2016 1:11:11 PM To: ropensci/rnoaa Cc: Anderson,Brooke; Mention Subject: Re: [ropensci/rnoaa] Additions from ROpenSci Unconference (Spring 2016) (#159)
thanks @geandershttps://github.com/geanders merged
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thanks for all your work on this, and the work of others, i'll add you as a contributor
This pull requests incorporates work started at the spring's ROpenSci Unconference. Specific elements of this pull request are:
rnoaa
to pull weather data that can then be used in conjunction with air pollution data pulled using OpenAQ ("rnoaa_openaq.RMD").meteo_nearby_stations
function, to identify stations near a latitude-longitude pair for Global Historical Climatology Network daily weather data (defined in "meteo_distance.R" file).meteo_pull_monitors
, to pull Global Historical Climatology Network daily weather data from multiple monitors with a single function call (defined in "helpers_ghcnd.R" file).meteo_show_cache
andmeteo_clear_cache
functions, for cache management (both files in "meteo_cache.r") (other functions we're adding do not rely on these functions).meteo_coverage
function to determine the coverage (percent of non-missing weather observations over dates pulled) for each weather monitor (in "meteo_utils.R" file), with its own method for plotting coverage.vis_miss
function to visualize missingness in a dataframe, including weather dataframes generated withrnoaa