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PyConES 2019 Alicante
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Sunday, October 6 • 11:50 - 12:30
Data Science meets Economy: how to meassure social impact from consumption data

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Companies fulfill the needs of the population through the goods and services than they produce. Therefore, companies impact society by selling products to individuals. To quantify this impact we can analyze people’s consumption. Although traditionally this consumption is measured through surveys, we took advantage of modern Data Science techniques to analyze big data sources of real consumption data.

In this talk I will explore some example of the economic and data science analysis that we developed in Python to understand people’s consumption. I will explain how we are able to apply Angus Deaton Elasticity Theory to Big Data showing which goods are first-necessity-goods for the Mexican population. I will introduce Manifold Learning techniques to cluster individuals into meaningful consumption groups that transcends demographic features. Finally, I will show how to analyze consumption data as a complex system to compute the real Maslow’s hierarchy of needs based on the sophistication of individual consumers.

Sunday October 6, 2019 11:50 - 12:30 CEST
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