Editing Community Data Science Workshops (Spring 2016)/Day 3 Projects/Twitter
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== Analyzing Tweet Data with Python == | == Analyzing Tweet Data with Python == | ||
Last week, the [[Community_Data_Science_Workshops_%28Spring_2016%29/Day_2_Projects/Twitter|Twitter API Session]] covered accessing data from the Twitter API, including accessing streaming data. After the session, we set up a streaming collection from the code you modified in the workshop to track all earthquake-related tweets. That stream captured 3.5GB of tweets (!). We've given you a sample of those tweets in the zipped file above. | |||
Our goal in this workshop is to use those tweets to answer questions. As always, we've suggested questions below, but the real goal is for you to find something that you find interesting from the data. | |||
Our goal in this workshop is to | |||
Your data consists of 1 Tweet per line encoded in JSON exactly as Twitter returns it. | Your data consists of 1 Tweet per line encoded in JSON exactly as Twitter returns it. |