Schulatlas Scraper

Install NodeJS +19, make sure you can run it from a terminal, e.g. CMD.EXE, or Bash/ZSH on Linux/macOS.

Then run

node scraper.js

This will generate 3 files:

• base.json, the original JSON data containing basic information for all schools
• schools.csv, the basic information for all schools transformed to CSV. Fields:
  • type: the school type, e.g. VS, AHS, etc.
  • skz: a seemingly unique identifier
  • desc: the description
  • coords: longitude/latitude separated by a comma
  • street: street address
  • zip: ZIP code
  • city: town or city
  • keeper: whether this is a public or private school
  • classes: number of classes
  • pupils: total number of pupils
  • male: number of male pupils
  • female: number of female pupils
• vs-left-to.csv: Information about how many pupils from a primary school left for what other school. For each from -> to pair, there is one row with the following fields:
  • type: "VS"
  • skz: unique identifier for the "from" school
  • desc: the description of the "from" school
  • coords: longitude/latitude separated by a comma of the "from" school
  • street: street address of the "from" school
  • zip: ZIP code of the "from" school
  • city: town or city of the "from" school
  • keeper: whether the "from" school is a public or private school
  • classes: number of classes of the "from" school
  • pupils: total number of pupils of the "from" school
  • male: number of male pupils of the "from" school
  • female: number of female pupils of the "from" school
  • lt_type: type of the "to" school
  • lt_skz: unique identifier of the "to" school (SKZ_LAUFEND in the original data)
  • lt_desc: description of the "to" school (BESCHREIBUNG in the original data)
  • lt_ipub_desc: another description of the "to" school (IPUB2_BESCHREIBUNG in the original data)
  • lt_street: street address of the "tp" school
  • lt_zip: ZIP code of the "to" school
  • lt_city: town or city of the "to" school