Re-ingest global-mobility — previous parquet unavailable for diff — card update

README.md

@@ -1,46 +1,219 @@
 ---
-license: other
-license_name: google-mobility-report
-license_link: https://www.google.com/covid19/mobility/data_documentation.html
-task_categories:
-- time-series-forecasting
+pretty_name: Google Community Mobility Reports — global daily
+license: cc-by-4.0
+size_categories:
+- 10M<n<100M
 tags:
-- epidemiology
-- mobility
-- covid-19
-- google
+- cadence-daily
+- geo-global
+- surveillance-mobility
+- tier-2
+- availability-inactive
+schema_version: '0.1'
+source_id: global-mobility
+source_url: https://www.google.com/covid19/mobility/
+manifest_section: §15.7
+surveillance_category: mobility
+pathogens: []
+availability: inactive
+availability_notes: Google ended data collection 2022-10-15. Historical CSV remains available; not updated.
+access_type: csv
+tier: 2
+cadence: daily
+geography_levels:
+- national
+- subnational-state
+- subnational-county
+- subnational-city
+geography_countries:
+- multiple
+gold_standard_for: []
+vintaged_version_of: null
+succeeds: null
+derived_from: []
+value_columns:
+- name: retail_and_recreation
+  unit: percent change vs. baseline
+  value_type: index
+  description: 'Daily % change in visits + length of stay at retail / recreation places
+
+    (restaurants, cafes, shopping centers, theme parks, museums, libraries,
+
+    cinemas) compared to the baseline (median value for the 5-week period
+
+    Jan 3 – Feb 6, 2020).
+
+    '
+  aggregation: mean
+- name: grocery_and_pharmacy
+  unit: percent change vs. baseline
+  value_type: index
+  description: Daily % change in visits to grocery markets, food warehouses, farmers' markets, specialty food shops, drug
+    stores, pharmacies.
+  aggregation: mean
+- name: parks
+  unit: percent change vs. baseline
+  value_type: index
+  description: Daily % change in visits to local parks, national parks, public beaches, marinas, dog parks, plazas, public
+    gardens.
+  aggregation: mean
+- name: transit_stations
+  unit: percent change vs. baseline
+  value_type: index
+  description: Daily % change in visits to public transport hubs (subway, bus, train stations).
+  aggregation: mean
+- name: workplaces
+  unit: percent change vs. baseline
+  value_type: index
+  description: Daily % change in visits to places of work.
+  aggregation: mean
+- name: residential
+  unit: percent change vs. baseline
+  value_type: index
+  description: 'Daily % change in time spent in places of residence. (Note: this is
+
+    length-of-stay, not visit count — different metric than the other five.)
+
+    '
+  aggregation: mean
+notes:
+  extra_columns:
+  - column: location_name
+    description: 'Most-specific populated source field — county name for county rows,
+
+      metro name for metro rows, ISO sub-region name for state rows, country
+
+      name for national rows. `location_id` is canonical.
+
+      '
+  interpretation_caveats:
+  - column: residential
+    caveat: 'Residential is reported as % change in *length of stay*, not visit
+
+      count. The other five categories are visit-based. Don''t sum or compare
+
+      directly across these two flavours.
+
+      '
+  - column: parks
+    caveat: 'Parks shows extreme seasonal cyclicity (winter vs. summer is a 200%+
+
+      swing in many countries) that reflects normal seasonality, not
+
+      pandemic-period behaviour change. Detrend before any pandemic analysis.
+
+      '
+  - column: workplaces
+    caveat: 'Holidays / weekends are baked into the baseline since the baseline is
+
+      a median across weekdays + weekends. Day-of-week cycles in the output
+
+      are real but reflect *deviation* from the comparable weekday''s baseline.
+
+      '
+  general: 'Aggregated, anonymised mobility signals derived from Google Maps Location
+
+    History data. Coverage is global at the national level; subnational depth
+
+    varies by country (US has county granularity, most others have ISO 3166-2
+
+    state-level only). Privacy threshold means small geographies / low-traffic
+
+    days are NaN.
+
+    '
+extra:
+  baseline_period: median value across Jan 3 – Feb 6, 2020 (5 weeks, per weekday)
+  collection_end_date: '2022-10-15'
+  source_columns_omitted: '`place_id` (Google internal place identifier — opaque), `sub_region_1`,
+
+    `sub_region_2`, `country_region`, `metro_area` (collapsed into the derived
+
+    `location_id` + `location_name`), `country_region_code`, `iso_3166_2_code`,
+
+    `census_fips_code` (likewise collapsed).
+
+    '
+computed:
+  last_ingested: '2026-04-26T12:14:44Z'
+  row_count: 11728497
+  time_coverage:
+  - start: '2020-02-15'
+    end: '2022-10-15'
+  geography_unit_count: 5306
+  observed_cadence_days: 1
+  missing_gaps: []
+  data_hash: 63d11fb60ba0adbb
 ---
-# Google Community Mobility Reports — Standardized Time Series
-
-This dataset contains the [Google Community Mobility Reports](https://www.google.com/covid19/mobility/), which show movement trends by region and category (Retail & recreation, Grocery & pharmacy, Parks, Transit stations, Workplaces, and Residential).
-
-### Coverage
-- **Time:** 2020-02-15 → 2022-10-15 (Official end of Google's data collection)
-- **Geography levels:** National and Subnational (State/County/Region)
-- **Countries:** Global (Multiple countries included)
-
-### Columns
-| Column | Unit | Description |
-| --- | --- | --- |
-| **date** | YYYY-MM-DD | Date of the report. |
-| **location_id** | String | ISO 3166-1 alpha-2 code or specific region code. |
-| **retail_and_recreation** | % change | Change in visits to places like restaurants, cafes, etc. |
-| **grocery_and_pharmacy** | % change | Change in visits to grocery markets and pharmacies. |
-| **transit_stations** | % change | Change in visits to public transport hubs. |
-| **workplaces** | % change | Change in visits to places of work. |
-
-### Interpretation Caveats
-- **Baseline:** The data shows how visits and stay length change compared to a baseline day (the median value for the 5-week period Jan 3–Feb 6, 2020).
-- **Privacy:** Google uses differential privacy to ensure no individual's movement can be identified. Some data points may be null if the privacy threshold isn't met.
-
-### Attribution
-This dataset is derived from the Google Community Mobility Reports.
-Citation: > Google LLC "Google Community Mobility Reports". https://www.google.com/covid19/mobility/ Accessed: April 25th, 2026
-
-### Access & Terms
-- **Availability:** This data is provided as-is for public health and research purposes.
-- **License:** Use of this data is subject to [Google's Terms of Service](https://policies.google.com/terms). 
-- **Tier:** 1
+
+# Google Community Mobility Reports — global daily
+
+Aggregated, anonymised mobility signals derived from Google Maps Location
+History data. Coverage is global at the national level; subnational depth
+varies by country (US has county granularity, most others have ISO 3166-2
+state-level only). Privacy threshold means small geographies / low-traffic
+days are NaN.
+
+**Source:** <https://www.google.com/covid19/mobility/>
+
+## Coverage
+
+- **Time:** 2020-02-15 → 2022-10-15
+- **Cadence:** `daily` (observed median spacing: 1 days)
+- **Geography levels:** `national`, `subnational-state`, `subnational-county`, `subnational-city` — 5306 unique location IDs
+- **Countries:** multiple
+- **Pathogens:** —
+- **Surveillance category:** `mobility`
+- **Rows:** 11,728,497
+
+## Columns
+
+| Column | Unit | value_type | Aggregation | Description |
+|--------|------|------------|-------------|-------------|
+| `retail_and_recreation` | percent change vs. baseline | `index` | `mean` | Daily % change in visits + length of stay at retail / recreation places
+(restaurants, cafes, shopping centers, theme parks, museums, libraries,
+cinemas) compared to the baseline (median value for the 5-week period
+Jan 3 – Feb 6, 2020).
+ |
+| `grocery_and_pharmacy` | percent change vs. baseline | `index` | `mean` | Daily % change in visits to grocery markets, food warehouses, farmers' markets, specialty food shops, drug stores, pharmacies. |
+| `parks` | percent change vs. baseline | `index` | `mean` | Daily % change in visits to local parks, national parks, public beaches, marinas, dog parks, plazas, public gardens. |
+| `transit_stations` | percent change vs. baseline | `index` | `mean` | Daily % change in visits to public transport hubs (subway, bus, train stations). |
+| `workplaces` | percent change vs. baseline | `index` | `mean` | Daily % change in visits to places of work. |
+| `residential` | percent change vs. baseline | `index` | `mean` | Daily % change in time spent in places of residence. (Note: this is
+length-of-stay, not visit count — different metric than the other five.)
+ |
+
+### Additional data columns
+
+- **`location_name`** — Most-specific populated source field — county name for county rows,
+metro name for metro rows, ISO sub-region name for state rows, country
+name for national rows. `location_id` is canonical.
+
+
+## Interpretation caveats
+
+Things that may differ from how other sources define a similar measure. If you're combining this dataset with another, read these first.
+
+- **`residential`** — Residential is reported as % change in *length of stay*, not visit
+count. The other five categories are visit-based. Don't sum or compare
+directly across these two flavours.
+
+- **`parks`** — Parks shows extreme seasonal cyclicity (winter vs. summer is a 200%+
+swing in many countries) that reflects normal seasonality, not
+pandemic-period behaviour change. Detrend before any pandemic analysis.
+
+- **`workplaces`** — Holidays / weekends are baked into the baseline since the baseline is
+a median across weekdays + weekends. Day-of-week cycles in the output
+are real but reflect *deviation* from the comparable weekday's baseline.
+
+
+## Access
+
+- **Availability:** `inactive`
+- **Access type:** `csv`
+- **License:** cc-by-4.0
+- **Tier:** 2
 
 ---
-*Schema version 0.1 · source_id: google-mobility*
+
+*Schema version `0.1` · Last ingested 2026-04-26T12:14:44Z · `source_id: global-mobility` · Manifest section §15.7*