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Category: GDAL

Tips for reading spatial files into R with rgdal

Posted on January 13, 2016 by zev@zevross.com · 2 Comments

R has become a go-to tool for spatial analysis in many settings. You can read and edit spatial data, conduct geoprocessing and spatial analysis and create static and interactive maps. Of course, the first step in spatial analysis with R is often reading in your spatial data and this step can be confusing and frustrating. […]

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No ESRI, no problem. Manipulate shapefiles with the Python library gdal

Posted on June 9, 2014 by zev@zevross.com · 3 Comments

Although we still use ESRI products such as ArcGIS for geographic analysis, more and more we find ourselves turning to open source software like PostGIS and QGIS. In many cases, though, even PostGIS and QGIS are more software than necessary for a given task and we prefer to skip the ‘middleman’ in favor of the […]

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R, Python, PostgreSQL (and more): A data science workflow example

Posted on April 29, 2014 by zev@zevross.com

Although many data science-related projects can be completed with a single software tool we often find that decisions about what tool to use for a project involve weighing a combination of what tool would be “best” for the job, what tools we're most familiar with and whether we already have scripts we can use. As […]

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PostgreSQL, R, US Census geography and encoding

Posted on March 20, 2014 by zev@zevross.com · Leave a comment

We use PostgreSQL/PostGIS to manage a lot of our tabular and geographic data from the US Census. In terms of workflow we will either download a shapefile manually from ftp://ftp.census.gov/geo/tiger/ or, if we’re dealing with more than one file (block groups or blocks for example), we will do this from within R (using the download.file() […]

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