1297 search results for "maps"

Using R and satellite data to identify marine bioregions

January 30, 2017
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Using R and satellite data to identify marine bioregions

R has become an essential tool in oceanography and marine ecology. For instance, R is specifically used to read, process and represent in situ oceanographic data and to manage satellite data in order to produce high temporal and spatial resolution maps useful to synoptically explore and monitoring vast areas of the world oceans. In this post we briefly describe...

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Metro Systems Over Time: Part 2

January 26, 2017
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Metro Systems Over Time: Part 2

Note, at the time of this writing using the packages ggplot2 and ggmap from CRAN will result in an error. To avoid the error be sure to install both packages from GitHub with the package devtools and restart R if the problem persists. devtools::install_github("dkahle/ggmap") devtools::install_github("hadley/ggplot2") Introduction In Part 1 of this series we collected geodata Related Post

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R Markdown for the Enterprise

January 25, 2017
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R Markdown for the Enterprise

by Edgar Ruiz In the corporate world, spreadsheets and PowerPoint presentations still dominate as the tools used for analyzing and sharing information. So, it is not at all surprising that even when business analysts use R for the analytical heavy lifting, they frequently revert to using spreadsheets and slide decks to share their results. This

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Extracting and Enriching Ocean Biogeographic Information System (OBIS) Data with R

January 25, 2017
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Extracting and Enriching Ocean Biogeographic Information System (OBIS) Data with R

Programmatic access to biodiversity data is revolutionising large-scale, reproducible biodiversity research. In the marine realm, the largest global database of species occurrence records is the Ocean Biogeographic Information System, OBIS. As of January 2017, OBIS contains 47.78 million occurrences of 117,345 species, all openly available and accessible via the OBIS API. The number of questions to address...

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Descriptive Analysis of MLST Data for MRSA

January 24, 2017
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Descriptive Analysis of MLST Data for MRSA

During one of my summers, I had the opportunity to conduct some research on the prevalence of methicillin-resistant Staphylococcus aureus (MRSA) in vulnerable populations and examining US emergency department data and I thought this would be a pretty interesting topic to expand on for my thesis in lieu of the increasing concerns of antimicrobial resistance, … Continue...

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Creating a “balloon plot” as alternative to a heat map with ggplot2

January 24, 2017
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Creating a “balloon plot” as alternative to a heat map with ggplot2

Heat maps are great to compare observations with lots of variables (which must be comparable in terms of unit, domain, … Read More →

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How to do an analysis in R (part 2, visualization and analysis)

January 24, 2017
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How to do an analysis in R (part 2, visualization and analysis)

In several recent blog posts, I've emphasized the importance of data analysis. My main point has been, that if you want to learn data science, you need to learn data analysis. Data analysis is the foundation of practical data science. With that statement in mind, I want to show you step-by-step what an analysis looks like in R ... The post...

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How to use viridis colors with plotly and leaflet?

“… avoiding catastrophe becomes the first principle in bringing color to information: Above all, do no harm.” - Envisioning Information, Edward Tufte, Graphics Press, 1990 Choosing colors for your plot is not so simple. Why is that so? First of all, it depends on numerous things… What plot are you creating? What is...

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readr::problems() returns tidy data!

January 23, 2017
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A handy little trick I picked up today when using readr. Some background: I needed a mapping between ZIP Code Tabulation Areas and counties (to link to some urban/rural data). The Census Bureau provides a CSV style table that includes information about each of the ZCTA (e.g.,...

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Metro Systems Over Time: Part 1

January 21, 2017
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Metro Systems Over Time: Part 1

Note, at the time of this writing using the packages ggplot2 and ggmap from CRAN will result in an error. To avoid the error be sure to install both packages from GitHub with the package devtools and restart R if the problem persists. devtools::install_github("dkahle/ggmap") devtools::install_github("hadley/ggplot2") Introduction Metro systems are an interesting way to learn more Related Post

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