Articles in this section

Atlas: Bulk CSV Export

1. Go to atlas.density.io

2. Navigate to the building and floor.

3. In the top right corner, select Export CSV. A box will appear with the options for your download.

4. Time Range: Directly click on the date range, operating hours, and days of the week shown in the area with the grey background to update these settings in a separate view. 

 

5. Time Resolution: Select between 1 day, 1 hour, 30-minute, or 15-minute time frames for your data to be displayed. The occupancy will show the average and the peak during the amount of time selected.

6. Spaces: Select between the space, floor, full building, or portfolio level of reporting. You will receive a zip file containing each level selected in its own file.

7. Include Floor and Building Occupancy Summary: This field is required to show Entry sensor data but can be used for all sensors. This will add the following reports:

  • Building level
  • Floor level
  • Space, floor, building level

8. The ZIP file will include (based on your CSV settings selection):

  • Labels: A list of the space IDs and associated labels

  • Spaces: Space metadata, time used percentage and minutes, average occupancy, and average density.

  • Building level: Occupancy average and peak for the building

  • Floor level: Occupancy average and peak for the floors

  • Space, floor, building level: Space metadata, time used percentage and minutes, average and peak occupancy, and average density.

9. For portfolio-level reporting, please note that there is not a separate portfolio CSV. The download will include:

  • Labels
  • Spaces (your selected floors will be included and shown in a separate column)
  • Building Level
  • Floor Level (your selected floors will be included and shown in a separate column)

Differences in Atlas CSV and Dashboard Analytics CSV Reports

​​File Names

  • Dashboard CSV is named according to the time series data it contains, with the date range included in the file name: density_time-series_1h_occupancy_2023-06-12_2023-06-16.csv.
  • Atlas CSV has a more detailed name reflecting the organization, location, time range, and type of data: Density Inc._San Francisco - 2 Bryant St_15min_20230403-20230622_8a-6p_floors.csv

Column Differences

The Legacy Dashboard file contains 4 columns:

  • "Space"
  • "Timestamp"
  • "Local Time"
  • "Occupancy"

The Atlas file contains 10 columns. It retains similar data to the Dashboard file but introduces additional details and a few changes:

  • "ORGANIZATION_NAME" and "ORGANIZATION_ID": Information about the organization not present in the Dashboard CSV
  • "FLOOR_NAME" and "FLOOR_ID": Details about the specific floor, which could be compared to the "Space" column in the Dashboard file, but with additional granularity and an ID.
  • "BUILDING_NAME" and "BUILDING_ID": The building details are similar to the "Space" column in the Dashboard CSV but with an additional ID.
  • "CAPACITY": This new column provides the total capacity of the floor or space.
  • "LOCAL_DATE_TIME": This is equivalent to the "Local Time" in the Dashboard CSV, but with a slightly different format ("YYYY-MM-DDTHH:MM:SS" vs. "YYYY-MM-DD HH:MM:SS") and without timezone offset.
  • "OCCUPANCY_AVG" and "OCCUPANCY_PEAK": These columns provide more detailed information about occupancy compared to the single "Occupancy" column in the Dashboard file.
  • "ENTRANCES" and "EXITS": These columns provide the entrance and exit count 

Key Takeaways

  • The Atlas file provides more detailed data than the Dashboard file.
  • The Atlas file introduces identifiers for organizations, floors, and buildings, which can be used for precise data tracking.
  • The Atlas file provides both average and peak occupancy information, whereas the Dashboard CSV only provides a single occupancy value.
  • The Atlas file includes a "CAPACITY" column, which wasn't available in the Dashboard file.
  • Time information in the Atlas file is without timezone offset, unlike the Dashboard file.
Was this article helpful?
0 out of 0 found this helpful

Comments

0 comments

Article is closed for comments.