Discussions

Hello. I am working with pass_by data that contains retail store visitors and visits information without the NAICS code, which makes it challenging to categorize POIs. My current approach to assigning NAICS categories is to leverage Placekey to link pass_by to SafeGraph. Then, I could use Brand Info from SafeGraph to determine the corresponding NAICS codes for each POI in pass_by.

Hi,

I am exploring the WageScape data and wondering what “Salary” and “Salary_modeled” exactly represent. I see the following descriptions for the two variables on Dewey:

I receive the following error when trying to install the 'deweydatar' package in R.

I noticed some fluctuations while plotting the average total spend and raw visit counts of some Starbucks stores we have pooled from our study.

Previsouly, I have been using bucketed_dwell_times ““<5”, “5-10”, “11-20”, “21-60”, “61-120”, “121- 240”, “>240””? In the recent filed I only observe “5-10”, “11-20”, and 61-120", “121-240”, can you please help me learn as the SafeGraph Doc says " * Data delivered from December 2020 onward, including all backfilled historical data, contains the following bins: { “<5”, “5-10”, “11-20”, “21-60”, “61-120”, “121-240”, “>240”} " on the safeGraph document page

Specifically, I have questions about the following columns: visitor_home_cbgs and visitor_daytime_cbgs. I would like to clarify the definitions of the "home city" and "home CBG" fields, as well as understand how these fields are censored.

Hi, I am analyzing the SafeGraph Spend Patterns dataset and noticed significant variations in store/branch coverage for some firms and brands over time.