A command-line tool to better visualize crowded dot density maps.
Don't miss the introductory blog post.
Developed as part of a visualization course at the University of Minnesota.
Have an idea? Open up an issue.
- Binify + D3 = Gorgeous honeycomb maps - Chris Wilson, Mechanical Scribe
- The Drone War: A Comprehesive Map of Lethal U.S. Attacks - Allsion McCann, Bloomberg Businessweek
- Crimes reported in Waterloo, Iowa - Chris Essig, Waterloo Cedar Falls Courier
Binify is available in the Python Package Index. I recommend using a virtual environment.
$ mkvirtualenv binify
$ pip install binify
Node: This installation assumes GDAL is already installed. To install GDAL with python bindings:
OS X: Try the precompiled biniaries by KyngChaos.
Ubuntu:
$ sudo apt-add-repository ppa:ubuntugis/ppa
$ sudo apt-get update
$ sudo apt-get install python-gdal
To view options for your installed version of Binify, use the help flag.
$ binify --help
usage: binify [-h] [-n NUM_ACROSS] [-o] [--ignore-type] infile outfile
positional arguments:
infile A point shapefile to create bins from.
outfile A shapefile to write to. Will be created if it does
not exist.
optional arguments:
-h, --help show this help message and exit
-n NUM_ACROSS, --num-across NUM_ACROSS
Number of hexagons for the grid to have across
(approximate)
-E EAST_LNG WEST_LNG SOUTH_LAT NORTH_LAT, --extent EAST_LNG WEST_LNG SOUTH_LAT NORTH_LAT
Use a custom extent.
-e, --exclude-empty Exclude shapes that end up binning zero points.
-o, --overwrite Overwrite output file.
--ignore-type Ignore the geometry type of the input shapefile.
--suppress-output Supress console output (excluding any warnings).
A basic execution may look like this:
$ binify MN_FFLS/MN_FFLS.shp MN_FFLS-grid/MN_FFLS-grid.shp