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Free foot traffic data12/31/2022 ![]() ![]() Each entry is a JSON object (or Python dictionary), where the key is a CBG and the value is the number of visitors seen who live in that CBG. The weekend_home_device_areas column is important, so let’s break it down a bit. We’ll just use weekend_device_home_areas in this article, but you can edit the code to use other columns as you see fit! The complete column list is available in the documentation. Neighborhood Patterns has a bunch of useful columns. Census Block Groups (CBGs) are the geographic areas that Neighborhood Patterns data are aggregated at - conveniently, Census data are also aggregated at the CBG level.Ī subset of the columns from SafeGraph Neighborhood Patterns. Specifically, we’ve filtered to the Census Block Group that contains the Des Moines Farmers Market. Let’s take a look at our data! The first DataFrame is the SafeGraph Neighborhood Patterns for downtown Des Moines. Feel free to check those code snippets out in the Colab notebook! For simplicity’s sake, we will skip some of the boring stuff (imports, installations, reading in the data, etc). To run the code and play with the data yourself, check out the accompanying Colab notebook ! Setupīefore every exciting analysis is a somewhat boring (yet important!) setup section. If you want to extend this analysis, or research your own problems using foot traffic data, visit the SafeGraph Community. Better yet, this dataset and others are free for academics. With Neighborhood Patterns, we can answer questions about the number of visitors, where they come from, how long they stayed, and more. Have no fear, Neighborhood Patterns is here! Vendor locations within the Farmers Market move from week to week.The Farmers Market only occupies the area on Saturdays during certain months. ![]()
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