This is great. I wonder if using this data patterns could be found showing when and where tickets are written. Would be interesting to know when and how often certain areas are checked for illegal parking, if such a pattern exists.
As an alternative to lxml or BeautifulSoup, I've used a library called PyQuery (https://pythonhosted.org/pyquery/) with some success. It has a very similar API to jQuery.
In my state that costs $10/bureau, plus another $10 to temporarily unfreeze or permanently unfreeze. The fact that they can leak my information and then charge me to protect myself just seems wrong.
You have the ability to hide specific endorsements - for instance, if someone endorses me for a skill that they don't actually know that I know, LinkedIn provides the ability to hide that person's endorsement.
I set up Ghost on a DO droplet the other day. Even opting to manually install it rather than use the Ghost on Ubuntu image, installation and setup was a breeze.
DRIVIN is looking to expand our data team as we continue to grow our data platform. The candidate should have a strong background with Python and SQL. As a member of the data team the main responsibilities are implementing/maintaining ETL jobs, using Python to ingest external data sources into the Data Warehouse, and working closely with the Product and Data Science teams to deliver data in usable formats and to the appropriate data sources.
DRIVIN has a polyglot data model using many cutting edge data platforms. We are currently using MPP Postgres (Greenplum, Netezza, DBX) as our Data Warehouse, Elastic Search for location based searching, Postgres for transactional data, and AeroSpike for Big Data.
This candidate should be a self-starter who is interested in learning new systems/environments and building new solutions.
They should also be interested in architecting simple, straight-forward solutions to reduce complex data problems. The candidate should also work closely with the Data Science team to identify interesting data points for use by the Data Science team.
DRIVIN tech stack is very cutting edge. MPP Postgres drives the Data Warehouse, ElasticSearch enables our location based searching/metrics, AeroSpike enables our Big Data storage, and Apache Spark is used to train our models. All environments are run off of AWS EC2/RDS/S3 and data processing framework is written in Python.