PHPMem v2.0.1
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1.6.45
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7 days 10 hours 39 minutes 43 seconds
Memory
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512MB
Used
13,32MB (2.6%)
Free
498,68MB
Keys
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10 162
Total (since start)
11 092
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157
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2 / 1 024 max
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66 054
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0
llm:851f9ce8b0e7a72b51fca757c1300bf1aa45b148d60e53ee66ea3ea62b9d5537
Edit
{
"action": "final",
"content": "## Geographic Distribution\n\nThis dataset **does** have a geographic dimension, captured in two tables:\n\n1. **`ip_geo`** — a reference table with 5 rows containing country/region/city/country_code fields\n2. **`nia_messages`** — conversation messages with an `author_geo` spatial field (5,297 total messages)\n\nHowever, **geographic coverage is extremely sparse**: only 197 of the 5,297 messages (~3.7%) have location data populated.\n\n### Distribution Across Locations\n\nAmong the 197 geotagged messages:\n\n- **119 messages (60%)** have **no country or region** recorded — only city-level data exists for these\n- **United States dominates** the identifiable records with 20 messages across 5 states:\n - California: 8 messages (7 from Menlo Park, 1 from San Jose)\n - Washington: 2 messages (Bellevue, Seattle)\n - Iowa, Nevada, Virginia: 1 message each\n- **India** accounts for 17 messages across 9 states/provinces (Telangana, Delhi, Karnataka, etc.)\n- **Other regions** include British Columbia (Canada) and England (UK) with 1 message each\n\n### Key Findings\n\n1. **Minimal geographic coverage** — 96.3% of messages lack location data entirely\n2. **U.S.-centric when present** — American locations represent the plurality of tagged messages\n3. **Data quality issues** — 60% of geotagged records are missing the country field, suggesting incomplete reverse-geocoding or partial IP resolution\n4. **Not suitable for geographic analysis** — with only 197 usable records and significant missing data, this dimension cannot support reliable location-based insights (e.g., usage by region, timezone patterns, or international adoption trends)\n\nThe geographic dimension exists structurally but is too incomplete to answer \"where\" questions about dataset activity or user distribution.",
"charts": [
{
"kind": "bar",
"x": "country",
"series": [
"record_count"
],
"title": "Messages by Country (where country is populated)"
}
]
}