Thursday, March 7, 2013

Querying and Analyzing Google Domestic Trends Data

Similar to Google Trends, Google Domestic Trends is a set of indices created by aggregating search volumes for groups of queries that are related to a specific sector.

In this IPython Notebook, I go through some statistical tests in Python with Google Domestic Trends data using searches by automotive buyers (queries such as "cars, kelly blue book, auto, used cars, toyota, autotrader") to try and predict the volume of search queries related to automotive financing (queries such as "lease, mileage, loan calculator, auto loan, car payment").

I also do some basic tests of periodicity in the data, as well as provide a Python wrapper for querying Google Domestic Trends to return a pandas DataFrame.

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