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Unveiling the potential of graph databases with Python and Neo4j


Every time we are dealing with data coming from the real world, big and not so big, you know that usually 80% of the time is needed to clean, prepare and arrange them. We can then spend the other 20% of the time enjoying our beloved data analysis.

The thing that you may know less is that in the last years, the Neo4j graph database went into the light of being the “right” place to store data, thanks to its capacity of direct modelling relations among data, its high availability and its easy, fast and clean query language Cypher.

In this talk I’m going to show you some tips to set up in the right way your data using Pandas, in order to proper model and import them into Neo4j. A Neo4j Python driver is available to easily import Cypher queries embedded in Python code. Still, the py2neo package allows building and querying your database right within your favourite snake command line.

Forget about “tall as teen” SQL queries here; thanks to Pandas, Python and Cypher modelling, loading and query your database is going to be really straightforward. After this talk, you’ll can’t wait to give Neo4j a try!

Prerequisite: a little knowledge of Pandas.

in __on venerdì 20 aprile at 11:45 **See schedule**


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