Discussions
Advan Weekly Patterns Plus: Sharp drop in evening visits Jan 2023 -- change in how hours are recorded?
I had a few questions about the new Advan Weekly Patterns Plus data.
How are median dwell times calculated in Advan Neighborhood Patterns data?
I am wondering how the "MEDIAN_DWELL" variable is calculated in the Advan Neighborhood Patterns dataset. The variable description is somewhat vague:
"exclude" filter doesn't seem to include rows with missing values
In order to get my download sizes under 5% (when downloading data from the Attom Tax Assessor dataset), I was previously using the filter for "MSANAME". However, when I use the exclude filter, it seems to ignore the MSA's I've listed (desired), but also ignore rows that are missing an MSANAME value (not desired, because I'm trying to get a complete universe of data). This either seems like a bug, or like a quirk that is not discussed anywhere, and could lead to incomplete datasets being downloaded. It seems intuitive to me that N/A values should be included when performing an 'exclude X value' filter, or to allow the inclusion/exclusion of N/A values as an additional filter. Is this something that can be addressed?
missing variables and inconsistent column names in Attom Tax Assessor downloads
I've been downloading 5% increments of the Attom Tax Assessor data over the span of several days, but noticed that the column names have inconsistencies between the batches I download. For instance, the Attom ID column is labeled "_ATTOM_ID_" for my Utah sample, but labeled "X_ATTOM_ID_" for my Nevada sample, and labeled "ATTOMID" for my California sample. I also noticed that the property latitude and longitude seemed to be missing from a sample I downloaded covering AZ, CO, ID, and WY (even though I've been selecting all columns to be downloaded).
Issue with Bulk API using Python - Foot Traffic / Weekly Patterns
Hi,
How are age and state filtering defined in Consumer Profiles and Address History?
Hello,
Duplicates in WageScape Title Data
I am working with WageScape's Title data, and I am noticing that there are millions of observations with identical Job Posting IDs, which the data dictionary suggests should be the unique job posting identifier. At a glance, it looks like there are 423M observations in WageScape's Job Postings With Salary database, 407M in Role Mapping, and 454 in Time Logs, yet there are 818M observations in Titles. What is the best way to handle these duplicates, and why are there so many? Are these duplicates the result of some job postings having multiple titles?