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Sixth meetup (Data science jobs and json transformations)

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Dear all,

We are thrilled to announce the sixth PyData Amsterdam meetup, and the first one in 2017!

KPMG (http://www.kpmg.nl) (food, drinks) and GoDataDriven (https://godatadriven.com) (venue) will be sponsoring this event. We thank them to be such an amazing help for the community!

First talk: Getting a job as a data scientist, by Giovanni Lanzani (GoDataDriven)

Abstract:

The 21th century sexiest job sure seems... sexy. Data scientists are more in demand than ever and it's hard to find a cv of a newcomer that doesn't say Kaggle or Machine Learning (Udacity/Coursera/Insert your own MOOC here). But what do companies really need and how can you exceed their need? A hand wavy introduction to the job market in applied data science (in the Dutch landscape)

Bio:

Giovanni arrived at GoDataDriven because the firm, although small at that time, made him an offer he couldn't refuse, stealing him from the Software Quality department of KPMG. A theoretical Physicist by trade (he claims he once received the title Doctor from Leiden University for his outstanding research in that field), he is now active as Chief Science Officer and Senior Shoe Designer.

Second Talk: Filling your data frame: a little library that just might make your life a bit easier, by Timo Kluck (Booking.com)

Abstract:

The first step for any analysis is taking the data in whatever format it is in, and projecting the entries onto an essentially two-dimensional data frame. Pandas tries to help! It provides `read_json`, `json_normalize` and `json.nested_to_record`. Oh, and also `DataFrame.from_dict`, `from_items` and `from_records`. Just don't forget what the `orient` parameter does (on all of them) or you may mix up your data! And what, again, was the difference between an 'item' and a 'record'?
I recently wrote a tiny library that makes it super-easy to specify these kinds of data transformations: without list comprehensions or loops; without remembering options; and without being limited to the transformations that have already been imagined for you.

Bio:

Timo Kluck is a Principal Developer at Booking.com, where he is responsible for the tooling driving data-driven product development (also known as A/B-testing). Trying to keep a healthly balance between training/education and writing code, he is a Perl developer by job description and a Python developer by heart. He has a background in mathematics.

Schedule

18.30 Doors open (Pizza & drinks)
19.00 Greetings & intro
19.15 First talk
20.00 Break
20.15 Second talk
20.45 Drinks
21:30 Meetup ends (building closes)

See you there!

Gabriele, Giovanni, Marcel, Mel and Vincent