Collecting, Analyzing, and Visualizing Data with Python Part II

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Presentation transcript:

Collecting, Analyzing, and Visualizing Data with Python Part II Dr. Michael Fire

Turi Create - SFrame Pandas In-memory data structure - cannot work (usually) with DataFrames bigger than the RAM Usually use a single thread Extensive functionality Well maintained Many tutorials TuriCreate Out-of-core data structure (uses both disk and memory) Multithreaded Can scale to big data Uses similar syntax to DataFrame Easy to understand and uses Group By function Well maintained (by Apple) Part of the Turi Create Platform

Turi Create in Practice I used SFrame to: Analyze Reddit dataset of with data of over 10 years Analyze Microsoft Academic Dataset with 120 million papers Analyze Amazon Reviews Dataset and more It is a great easy-to-use tool to work with Big Data. Let’s move to running code using Jupyter Notebook

Recommended Reading TuriCreate Userguide TuriCreate API - turicreate.SFrame A Guide to Turi Create - WWDC 2018 - Videos - Apple Developer