Python and Graph Databases & Pandas Power

We will have a talk on Graph Databases and python.

And we will have another talk on Pandas.

First on the databases:

You know about Python. Graph databases are one of the most fascinating NoSQL DB. The intro to the Wikipedia (http://en.wikipedia.org/wiki/Graph_database) article gives a good overview:

Compared with relational databases, graph databases are often faster for associative data sets[citation needed], and map more directly to the structure of object-oriented applications. They can scale more naturally to large data sets as they do not typically require expensive join operations. As they depend less on a rigid schema, they are more suitable to manage ad hoc and changing data with evolving schemas. Conversely, relational databases are typically faster at performing the same operation on large numbers of data elements.Graph databases are a powerful tool for graph-like queries, for example computing the shortest path between two nodes in the graph. Other graph-like queries can be performed over a graph database in a natural way (for example graph's diameter computations or community detection).

Martin will gives us the ins and out of GraphDBs. Enjoy!

And afterwards, we will have a talk on the ins and outs of Pandas. Balaz will present: Data Visualization, Pattern Searching and Outlier Detection with Python and Pandas

You know Pandas? Then you should come and learn more? You don't know Pandas? Time to get started Look at the Tutorial (http://pandas.pydata.org/pandas-docs/version/0.15.1/10min.html) to see what is possible, learn more from the talk!