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Visualization and analysis of hate crime in Berlin, with data provided by ReachOut - Opferberatung und Bildung gegen Rechtsextremismus, Rassismus und Antisemitismus
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Joshua Widmann 88e0b27285 autoprefix style.css and better categorizing.
2015-02-09 09:49:31 +01:00
scraper Clean up code, clarify and remove an unnecessary try-except-block 2014-12-11 00:29:08 +01:00
stanford-postagger-full-2014-10-26 Start messing around with part of speech tagging 2015-01-17 15:15:51 +01:00
static autoprefix style.css and better categorizing. 2015-02-09 09:49:31 +01:00
views More cosmetics 2015-02-09 00:50:33 +01:00
.editorconfig Use peewee as model and rewrite the code 2014-12-10 23:56:27 +01:00
.gitignore Use JSPM for frontend JS modules 2015-02-08 09:49:17 +01:00
analyze.py autoprefix style.css and better categorizing. 2015-02-09 09:49:31 +01:00
german_nouns.txt Use list of german nouns before geocoding 2015-02-07 14:53:27 +01:00
get_incidents.py swapped '…' with '...' and removed sqlite3 import. 2015-01-17 13:58:38 +01:00
locator.py Use list of german nouns before geocoding 2015-02-07 14:53:27 +01:00
models.py Remove unused model strinigfication 2015-02-07 17:38:48 +01:00
package.json Use JSPM for frontend JS modules 2015-02-08 09:49:17 +01:00
README.md Add potentially interesting statistics 2015-02-07 14:53:09 +01:00
requirements.txt Add more server APIs 2015-02-07 17:37:27 +01:00
server.py fixed noncategorized filter 2015-02-08 15:47:45 +01:00

README.md

What is this?

A visualization of hate crime in Berlin, starting 2005. The data is kindly provided by ReachOut - Opferberatung und Bildung gegen Rechtsextremismus, Rassismus und Antisemitismus. It is scraped regularly from their webpage and visualized and analyzed by software written by Joshua Widmann and Arne Schlüter.

How do I start?

In order to set up the tables you have to create them first. This is done quite easily using the python interpreter:

from models import *
create_tables()

Interesting statistics

  1. How often did violence occur?
  2. Where did it occur the most?
  3. How do we categorize it?
  4. How many did occur close train stations?