- Could not load data from data source arcgis file too big install#
- Could not load data from data source arcgis file too big drivers#
- Could not load data from data source arcgis file too big zip#
To read or write a specific file type you need to make sure that you have the drivers installed. But, if possible, I prefer to use one function, one package for reading spatial files and so this post focuses on readOGR. Keep in mind that there are several specialty packages for reading or writing various formats (e.g., geojsonio, plotKML) that you might consider using and I use occasinoally.
Could not load data from data source arcgis file too big install#
You need to install the rgdal package before you can run any of the code in this post. The rgdal package has been around for more than a decade and provides bindings to the incredible Geospatial Data Abstraction Library (GDAL) for reading, writing and converting between spatial formats.
Could not load data from data source arcgis file too big zip#
You can download the files I use in the post as a ZIP here. An example of using the raster function can be found in our post on analyzing raster data in R. For raster data I use the raster package rather than readGDAL from rgdal and I find that these functions ( raster, brick and stack) are more straightforward and work smoothly. Note that this post is limited to reading and writing vector data. This post focuses on four formats that are among the most common: shapefiles, MapInfo files, GeoJSON and GPS (with a GPX extension). Navigating these oddities is daunting but once you learn the syntax for the limited number of file types you likely work you’ll be able to comfortably move on to the fun of spatial analysis in R.
That trailing backslash is toxic and I'll bet that this single idiosynchrasy has prevented more than one researcher from conducting spatial analysis in R. ReadOGR(dsn="x:/junk/", layer="myfile") # fail As an example, you might surprised to learn that one of these lines of code for reading a shapefile will work fine and one will fail can you guess which is which? readOGR(dsn="x:/junk", layer="myfile") # works fine You can use this function to read in dozens of different formats but the syntax can be odd and, importantly, is different for different input types. The super-powerful grandfather of functions for reading vector-based spatial data is readOGR from the package rgdal. 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. You can read and edit spatial data, conduct geoprocessing and spatial analysis and create static and interactive maps. R has become a go-to tool for spatial analysis in many settings.