You are welcome to view and try our out-of-the-box Python notebooks for the following cases

About the sample

The goal of this notebook is to pull data points for a chain or tag (comprised of venues or complexes) to approximate the dashboard export as best as possible.

This notebook delivers data for the full-time frame.

Other notebooks deliver other granularities such as weekly,monthly, or daily.

The output of this code is a CSV file with:

One record for each entity (venue/complex)
Entity metadata for each record
Estimated visits/panel visits for the full time period
Hourly visits (optional)
Days-of-week distributed visitations

Dwell time data (optional)
Trade area demographics (optional, update parameter for different datasets)
Rankings (optional, chain or category rankings)

Visitations distributed by the trade area CBGs

Sample 1: Monthly granularity dashboard

Sample 2: Weekly granularity dashboard

This notebook accesses the Placer API endpoints for a chain or tag (comprised of venues or complexes) on a weekly granularity csv export.

The output of this code is a CSV file with:

One record per week for each entity (venue/complex)
Entity metadata for each record
Estimated visits/panel visits for each month
Hourly visits (optional)
Dwell time data (optional)
Trade area demographics (optional, update parameter for different datasets)
Rankings (optional, chain or category rankings)

Sample 2: Weekly granularity dashboard