diff --git a/data/internet/README.md b/data/internet/README.md new file mode 100644 index 000000000..ae70931f9 --- /dev/null +++ b/data/internet/README.md @@ -0,0 +1,23 @@ +# data/internet/ — internet use below the country level + +Source files for `data/tables/internet-by-adm1.json`, which +`plugin-designs/cities-internet/scripts/build-adm1-internet.mjs` writes. Edit the sources here and +re-run the script; never edit the table by hand. + +## nfhs5-internet-by-state.csv +- **What:** India, National Family Health Survey 5 (NFHS-5, 2019–21, IIPS / Ministry of Health and + Family Welfare), indicators 18 and 19: *Women / Men (age 15–49) who have ever used the internet (%)*, + by state/UT, urban / rural / total (plus the NFHS-4 total). +- **From:** the two internet rows of `NFHS-5-States.csv` in https://github.com/pratapvardhan/NFHS-5 at + commit `93c67fed2403c8e533d178d293c5ba0411892b1e`, a CSV transcription of the official state fact sheets + (http://rchiips.org/nfhs/). The transcriber notes that quality checks were minimal; the figures + here were spot-checked against the national fact sheet (India: women 33.3%, men 57.1%). +- **Licence:** the CSV is **CC BY 4.0**. Attribution: "NFHS-5 (IIPS/MoHFW) state fact sheets, via + pratapvardhan/NFHS-5 (CC BY 4.0)". +- **Measure:** a SURVEY SHARE OF PEOPLE (0–100%): has this person ever used the internet. It is + not a subscription count (TRAI's "subscribers per 100" is a different measure and can exceed 100). + +## adm1-crosswalk-IND.json +Source state names → the `shapeName` of `plugin-designs/my-upg-100-list/data/gb-IND-ADM1.geojson` +(served as `assets/boundaries/gb-IND-ADM1.geojson`). Every source name must appear here, with either +the boundary name or `null` plus a reason. The build fails on anything else, never guesses. diff --git a/data/internet/adm1-crosswalk-IND.json b/data/internet/adm1-crosswalk-IND.json new file mode 100644 index 000000000..61c0d8139 --- /dev/null +++ b/data/internet/adm1-crosswalk-IND.json @@ -0,0 +1,120 @@ +{ + "_about": "NFHS-5 state name -> gb-IND-ADM1.geojson shapeName. null = no geometry to draw it on, with the reason. Checked by build-adm1-internet.mjs.", + "map": { + "Andaman & Nicobar Islands": { + "adm1": "Andaman and Nicobar Islands" + }, + "Andhra Pradesh": { + "adm1": "Andhra Pradesh" + }, + "Arunachal Pradesh": { + "adm1": "Arunāchal Pradesh" + }, + "Assam": { + "adm1": "Assam" + }, + "Bihar": { + "adm1": "Bihār" + }, + "Chandigarh": { + "adm1": "Chandīgarh" + }, + "Chhattisgarh": { + "adm1": "Chhattīsgarh" + }, + "Dadra & Nagar Haveli and Daman & Diu": { + "adm1": "Dādra and Nagar Haveli and Damān and Diu" + }, + "Goa": { + "adm1": "Goa" + }, + "Gujarat": { + "adm1": "Gujarāt" + }, + "Haryana": { + "adm1": "Haryāna" + }, + "Himachal Pradesh": { + "adm1": "Himāchal Pradesh" + }, + "India": { + "adm1": null, + "national": true, + "reason": "the national row, kept as the national reference" + }, + "Jammu & Kashmir": { + "adm1": "Jammu and Kashmīr" + }, + "Jharkhand": { + "adm1": "Jhārkhand" + }, + "Karnataka": { + "adm1": "Karnātaka" + }, + "Kerala": { + "adm1": "Kerala" + }, + "Ladakh": { + "adm1": "Ladākh" + }, + "Lakshadweep": { + "adm1": "Lakshadweep" + }, + "Madhya Pradesh": { + "adm1": "Madhya Pradesh" + }, + "Maharashtra": { + "adm1": "Mahārāshtra" + }, + "Manipur": { + "adm1": "Manipur" + }, + "Meghalaya": { + "adm1": "Meghālaya" + }, + "Mizoram": { + "adm1": null, + "reason": "excluded from the shipped boundary file, which is the UPG-100 partition (my-upg-100-list/data/source-boundaries.mjs: 36 units upstream, 34 on disk)" + }, + "NCT Delhi": { + "adm1": "Delhi" + }, + "Nagaland": { + "adm1": null, + "reason": "excluded from the shipped boundary file, which is the UPG-100 partition (my-upg-100-list/data/source-boundaries.mjs: 36 units upstream, 34 on disk)" + }, + "Odisha": { + "adm1": "Odisha" + }, + "Puducherry": { + "adm1": "Puducherry" + }, + "Punjab": { + "adm1": "Punjab" + }, + "Rajasthan": { + "adm1": "Rājasthān" + }, + "Sikkim": { + "adm1": "Sikkim" + }, + "Tamil Nadu": { + "adm1": "Tamil Nādu" + }, + "Telangana": { + "adm1": "Telangāna" + }, + "Tripura": { + "adm1": "Tripura" + }, + "Uttar Pradesh": { + "adm1": "Uttar Pradesh" + }, + "Uttarakhand": { + "adm1": "Uttarākhand" + }, + "West Bengal": { + "adm1": "West Bengal" + } + } +} \ No newline at end of file diff --git a/data/internet/nfhs5-internet-by-state.csv b/data/internet/nfhs5-internet-by-state.csv new file mode 100644 index 000000000..7717daada --- /dev/null +++ b/data/internet/nfhs5-internet-by-state.csv @@ -0,0 +1,75 @@ +state,state_code,indicator,nfhs5_urban,nfhs5_rural,nfhs5_total,nfhs4_total +India,,18. Women who have ever used the internet (%),51.8,24.6,33.3, +India,,19. Men who have ever used the internet (%),72.5,48.7,57.1, +Andaman & Nicobar Islands,AN,18. Women who have ever used the internet (%),44.1,27.9,34.8, +Andaman & Nicobar Islands,AN,19. Men who have ever used the internet (%),54.6,41.1,46.5, +Andhra Pradesh,AP,18. Women who have ever used the internet (%),33.9,15.4,21.0, +Andhra Pradesh,AP,19. Men who have ever used the internet (%),65.1,41.5,48.8, +Arunachal Pradesh,AR,18. Women who have ever used the internet (%),70.0,49.6,52.9, +Arunachal Pradesh,AR,19. Men who have ever used the internet (%),86.9,68.5,71.6, +Assam,AS,18. Women who have ever used the internet (%),49.0,24.4,28.2, +Assam,AS,19. Men who have ever used the internet (%),67.4,37.8,42.3, +Bihar,BR,18. Women who have ever used the internet (%),38.4,17.0,20.6, +Bihar,BR,19. Men who have ever used the internet (%),58.4,39.4,43.6, +Chandigarh,CH,18. Women who have ever used the internet (%),75.2,,75.2, +Chandigarh,CH,19. Men who have ever used the internet (%),91.9,,91.9, +Chhattisgarh,CT,18. Women who have ever used the internet (%),44.5,20.8,26.7, +Chhattisgarh,CT,19. Men who have ever used the internet (%),75.4,50.4,56.3, +Dadra & Nagar Haveli and Daman & Diu,DD,18. Women who have ever used the internet (%),49.4,23.8,36.7, +Dadra & Nagar Haveli and Daman & Diu,DD,19. Men who have ever used the internet (%),76.2,61.3,68.3, +NCT Delhi,DL,18. Women who have ever used the internet (%),63.7,69.2,63.8, +NCT Delhi,DL,19. Men who have ever used the internet (%),85.1,87.4,85.2, +Goa,GA,18. Women who have ever used the internet (%),78.1,68.3,73.7, +Goa,GA,19. Men who have ever used the internet (%),86.1,76.6,82.9, +Gujarat,GJ,18. Women who have ever used the internet (%),48.9,17.5,30.8, +Gujarat,GJ,19. Men who have ever used the internet (%),72.9,48.0,58.9, +Himachal Pradesh,HP,18. Women who have ever used the internet (%),78.9,45.2,49.7, +Himachal Pradesh,HP,19. Men who have ever used the internet (%),83.7,65.1,67.9, +Haryana,HR,18. Women who have ever used the internet (%),60.2,42.8,48.4, +Haryana,HR,19. Men who have ever used the internet (%),79.7,68.8,72.4, +Jharkhand,JH,18. Women who have ever used the internet (%),57.8,22.7,31.4, +Jharkhand,JH,19. Men who have ever used the internet (%),70.8,53.2,58.0, +Jammu & Kashmir,JK,18. Women who have ever used the internet (%),55.0,38.9,43.3, +Jammu & Kashmir,JK,19. Men who have ever used the internet (%),79.4,68.8,72.0, +Karnataka,KA,18. Women who have ever used the internet (%),50.1,24.8,35.0, +Karnataka,KA,19. Men who have ever used the internet (%),71.5,55.6,62.4, +Kerala,KL,18. Women who have ever used the internet (%),64.9,57.5,61.1, +Kerala,KL,19. Men who have ever used the internet (%),78.3,74.2,76.1, +Lakshadweep,LD,18. Women who have ever used the internet (%),61.8,36.0,56.4, +Lakshadweep,LD,19. Men who have ever used the internet (%),81.5,77.0,80.3, +Ladakh,LH,18. Women who have ever used the internet (%),66.5,54.0,56.4, +Ladakh,LH,19. Men who have ever used the internet (%),82.9,64.3,67.8, +Maharashtra,MH,18. Women who have ever used the internet (%),54.3,23.7,38.0, +Maharashtra,MH,19. Men who have ever used the internet (%),76.8,47.2,61.5, +Meghalaya,ML,18. Women who have ever used the internet (%),57.8,28.0,34.7, +Meghalaya,ML,19. Men who have ever used the internet (%),59.2,38.5,42.1, +Manipur,MN,18. Women who have ever used the internet (%),50.8,40.4,44.8, +Manipur,MN,19. Men who have ever used the internet (%),81.5,68.2,73.9, +Madhya Pradesh,MP,18. Women who have ever used the internet (%),46.5,20.1,26.9, +Madhya Pradesh,MP,19. Men who have ever used the internet (%),72.7,49.3,55.7, +Mizoram,MZ,18. Women who have ever used the internet (%),83.8,48.0,67.6, +Mizoram,MZ,19. Men who have ever used the internet (%),92.7,63.9,79.7, +Nagaland,NL,18. Women who have ever used the internet (%),66.5,40.3,49.9, +Nagaland,NL,19. Men who have ever used the internet (%),81.0,55.2,64.6, +Odisha,OR,18. Women who have ever used the internet (%),39.7,21.3,24.9, +Odisha,OR,19. Men who have ever used the internet (%),64.2,47.2,50.7, +Punjab,PB,18. Women who have ever used the internet (%),64.1,48.8,54.8, +Punjab,PB,19. Men who have ever used the internet (%),85.6,73.0,78.2, +Puducherry,PY,18. Women who have ever used the internet (%),66.9,50.4,61.9, +Puducherry,PY,19. Men who have ever used the internet (%),85.1,69.4,80.7, +Rajasthan,RJ,18. Women who have ever used the internet (%),56.1,30.8,36.9, +Rajasthan,RJ,19. Men who have ever used the internet (%),81.7,59.4,65.2, +Sikkim,SK,18. Women who have ever used the internet (%),90.0,68.1,76.7, +Sikkim,SK,19. Men who have ever used the internet (%),94.2,69.5,78.2, +Telangana,TG,18. Women who have ever used the internet (%),43.9,15.8,26.5, +Telangana,TG,19. Men who have ever used the internet (%),72.3,46.7,57.4, +Tamil Nadu,TN,18. Women who have ever used the internet (%),55.8,39.2,46.9, +Tamil Nadu,TN,19. Men who have ever used the internet (%),76.1,64.9,70.2, +Tripura,TR,18. Women who have ever used the internet (%),36.6,17.7,22.9, +Tripura,TR,19. Men who have ever used the internet (%),47.0,45.2,45.7, +Uttar Pradesh,UP,18. Women who have ever used the internet (%),50.2,24.5,30.6, +Uttar Pradesh,UP,19. Men who have ever used the internet (%),72.4,54.2,59.1, +Uttarakhand,UT,18. Women who have ever used the internet (%),58.4,39.4,45.1, +Uttarakhand,UT,19. Men who have ever used the internet (%),82.1,71.2,74.6, +West Bengal,WB,18. Women who have ever used the internet (%),48.1,14.0,25.5, +West Bengal,WB,19. Men who have ever used the internet (%),64.6,38.3,46.7, diff --git a/data/tables/internet-by-adm1.json b/data/tables/internet-by-adm1.json new file mode 100644 index 000000000..ba5703316 --- /dev/null +++ b/data/tables/internet-by-adm1.json @@ -0,0 +1,2449 @@ +{ + "meta": { + "title": "Internet use by first-level administrative area", + "grain": "one row per iso3 x adm1 x measure x sex x area", + "measures": { + "ever_used_internet": { + "label": "Ever used the internet", + "unit": "%", + "population": "people aged 15–49, women and men asked separately", + "note": "A survey SHARE OF PEOPLE (0–100). Not a subscription count: never put it on one scale with subscriptions per 100." + } + }, + "sources": { + "nfhs5": { + "name": "National Family Health Survey 5 (NFHS-5), IIPS / Ministry of Health and Family Welfare, India", + "year": "2019-21", + "url": "http://rchiips.org/nfhs/", + "via": "https://github.com/pratapvardhan/NFHS-5 (CSV transcription of the state fact sheets)", + "licence": "CC BY 4.0", + "attribution": "NFHS-5 (IIPS/MoHFW) state fact sheets, via pratapvardhan/NFHS-5 (CC BY 4.0)" + } + }, + "boundaries": { + "IND": { + "file": "boundaries/gb-IND-ADM1.geojson", + "key": "shapeName", + "licence": "geoBoundaries gbOpen, India ADM1: CC BY 2.5 IN (datameet)", + "missing": [ + "Mizoram", + "Nagaland" + ], + "missing_reason": "no geometry in the shipped boundary file (the UPG-100 partition: 34 of 36 units)" + } + }, + "national": [ + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 33.3, + "source": "nfhs5", + "year": "2019-21" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 51.8, + "source": "nfhs5", + "year": "2019-21" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 24.6, + "source": "nfhs5", + "year": "2019-21" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 57.1, + "source": "nfhs5", + "year": "2019-21" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 72.5, + "source": "nfhs5", + "year": "2019-21" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 48.7, + "source": "nfhs5", + "year": "2019-21" + } + ], + "generated_by": "plugin-designs/cities-internet/scripts/build-adm1-internet.mjs" + }, + "rows": [ + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 34.8, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andaman and Nicobar Islands", + "adm1_name": "Andaman & Nicobar Islands" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 44.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andaman and Nicobar Islands", + "adm1_name": "Andaman & Nicobar Islands" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 27.9, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andaman and Nicobar Islands", + "adm1_name": "Andaman & Nicobar Islands" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 46.5, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andaman and Nicobar Islands", + "adm1_name": "Andaman & Nicobar Islands" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 54.6, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andaman and Nicobar Islands", + "adm1_name": "Andaman & Nicobar Islands" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 41.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andaman and Nicobar Islands", + "adm1_name": "Andaman & Nicobar Islands" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 21, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andhra Pradesh", + "adm1_name": "Andhra Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 33.9, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andhra Pradesh", + "adm1_name": "Andhra Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 15.4, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andhra Pradesh", + "adm1_name": "Andhra Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 48.8, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andhra Pradesh", + "adm1_name": "Andhra Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 65.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andhra Pradesh", + "adm1_name": "Andhra Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 41.5, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Andhra Pradesh", + "adm1_name": "Andhra Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 52.9, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Arunāchal Pradesh", + "adm1_name": "Arunachal Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 70, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Arunāchal Pradesh", + "adm1_name": "Arunachal Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 49.6, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Arunāchal Pradesh", + "adm1_name": "Arunachal Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 71.6, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Arunāchal Pradesh", + "adm1_name": "Arunachal Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 86.9, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Arunāchal Pradesh", + "adm1_name": "Arunachal Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 68.5, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Arunāchal Pradesh", + "adm1_name": "Arunachal Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 28.2, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Assam", + "adm1_name": "Assam" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 49, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Assam", + "adm1_name": "Assam" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 24.4, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Assam", + "adm1_name": "Assam" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 42.3, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Assam", + "adm1_name": "Assam" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 67.4, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Assam", + "adm1_name": "Assam" + }, + { + "iso3": "IND", + "measure": 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"adm1_name": "Tamil Nadu" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 70.2, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Tamil Nādu", + "adm1_name": "Tamil Nadu" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 76.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Tamil Nādu", + "adm1_name": "Tamil Nadu" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 64.9, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Tamil Nādu", + "adm1_name": "Tamil Nadu" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 22.9, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Tripura", + "adm1_name": "Tripura" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 36.6, + "source": "nfhs5", + "year": 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"year": "2019-21", + "adm1": "Uttar Pradesh", + "adm1_name": "Uttar Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 50.2, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttar Pradesh", + "adm1_name": "Uttar Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 24.5, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttar Pradesh", + "adm1_name": "Uttar Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 59.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttar Pradesh", + "adm1_name": "Uttar Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 72.4, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttar Pradesh", + "adm1_name": "Uttar Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 54.2, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttar Pradesh", + "adm1_name": "Uttar Pradesh" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 45.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttarākhand", + "adm1_name": "Uttarakhand" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 58.4, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttarākhand", + "adm1_name": "Uttarakhand" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 39.4, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttarākhand", + "adm1_name": "Uttarakhand" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 74.6, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttarākhand", + "adm1_name": "Uttarakhand" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 82.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttarākhand", + "adm1_name": "Uttarakhand" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 71.2, + "source": "nfhs5", + "year": "2019-21", + "adm1": "Uttarākhand", + "adm1_name": "Uttarakhand" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "total", + "value": 25.5, + "source": "nfhs5", + "year": "2019-21", + "adm1": "West Bengal", + "adm1_name": "West Bengal" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "urban", + "value": 48.1, + "source": "nfhs5", + "year": "2019-21", + "adm1": "West Bengal", + "adm1_name": "West Bengal" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "women", + "area": "rural", + "value": 14, + "source": "nfhs5", + "year": "2019-21", + "adm1": "West Bengal", + "adm1_name": "West Bengal" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "total", + "value": 46.7, + "source": "nfhs5", + "year": "2019-21", + "adm1": "West Bengal", + "adm1_name": "West Bengal" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "urban", + "value": 64.6, + "source": "nfhs5", + "year": "2019-21", + "adm1": "West Bengal", + "adm1_name": "West Bengal" + }, + { + "iso3": "IND", + "measure": "ever_used_internet", + "sex": "men", + "area": "rural", + "value": 38.3, + "source": "nfhs5", + "year": "2019-21", + "adm1": "West Bengal", + "adm1_name": "West Bengal" + } + ] +} diff --git a/library/i18n/locales/ar/connectivity.json b/library/i18n/locales/ar/connectivity.json index bccff8fba..2d5402e9d 100644 --- a/library/i18n/locales/ar/connectivity.json +++ b/library/i18n/locales/ar/connectivity.json @@ -54,5 +54,15 @@ "messaging": "تطبيقات المراسلة" }, "loading": "جارٍ تحميل {name}…" + }, + "adm1": { + "title": "الهند حسب الولاية: سبق لهم استخدام الإنترنت", + "women": "النساء", + "men": "الرجال", + "total": "الإجمالي", + "urban": "الحضر", + "rural": "الريف", + "source": "المسح NFHS-5 (2019–2021)، الأشخاص من 15 إلى 49 عامًا: نسبة من سبق لهم استخدام الإنترنت. مسح للأشخاص، لا عدد للاشتراكات.", + "missing": "لا توجد بعد حدود ولاية لـ {names}: أرقامها موجودة في البيانات، لا على الخريطة." } } diff --git a/library/i18n/locales/de/connectivity.json b/library/i18n/locales/de/connectivity.json index d982b5d8e..7d755ea09 100644 --- a/library/i18n/locales/de/connectivity.json +++ b/library/i18n/locales/de/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Messenger" }, "loading": "{name} wird geladen…" + }, + "adm1": { + "title": "Indien nach Bundesstaat: haben das Internet schon genutzt", + "women": "Frauen", + "men": "Männer", + "total": "Gesamt", + "urban": "Stadt", + "rural": "Land", + "source": "NFHS-5 (2019–21), Personen im Alter von 15–49 Jahren: Anteil derer, die das Internet schon einmal genutzt haben. Eine Befragung von Menschen, keine Zählung von Anschlüssen.", + "missing": "Noch keine Staatsgrenze für {names}: Ihre Werte stehen in den Daten, nicht auf der Karte." } } diff --git a/library/i18n/locales/en/connectivity.json b/library/i18n/locales/en/connectivity.json index 52a3fa864..fb72fdf42 100644 --- a/library/i18n/locales/en/connectivity.json +++ b/library/i18n/locales/en/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Messaging Apps" }, "loading": "Loading {name}…" + }, + "adm1": { + "title": "India by state: ever used the internet", + "women": "Women", + "men": "Men", + "total": "Total", + "urban": "Urban", + "rural": "Rural", + "source": "NFHS-5 (2019–21), people aged 15–49: the share who have ever used the internet. A survey of people, not a count of subscriptions.", + "missing": "No state boundary yet for {names}: their figures are in the data, not on the map." } } diff --git a/library/i18n/locales/es/connectivity.json b/library/i18n/locales/es/connectivity.json index 10164c444..5a68d35e5 100644 --- a/library/i18n/locales/es/connectivity.json +++ b/library/i18n/locales/es/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Mensajería" }, "loading": "Cargando {name}…" + }, + "adm1": { + "title": "India por estado: han usado internet alguna vez", + "women": "Mujeres", + "men": "Hombres", + "total": "Total", + "urban": "Urbano", + "rural": "Rural", + "source": "NFHS-5 (2019–21), personas de 15 a 49 años: proporción que ha usado internet alguna vez. Una encuesta a personas, no un recuento de suscripciones.", + "missing": "Aún no hay límite estatal para {names}: sus cifras están en los datos, no en el mapa." } } diff --git a/library/i18n/locales/fr/connectivity.json b/library/i18n/locales/fr/connectivity.json index 902c2581c..71488ebbe 100644 --- a/library/i18n/locales/fr/connectivity.json +++ b/library/i18n/locales/fr/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Messageries" }, "loading": "Chargement de {name}…" + }, + "adm1": { + "title": "Inde par État : ont déjà utilisé Internet", + "women": "Femmes", + "men": "Hommes", + "total": "Total", + "urban": "Urbain", + "rural": "Rural", + "source": "NFHS-5 (2019–21), personnes de 15 à 49 ans : part de celles qui ont déjà utilisé Internet. Une enquête auprès des personnes, pas un décompte d’abonnements.", + "missing": "Pas encore de limite d’État pour {names} : leurs chiffres figurent dans les données, pas sur la carte." } } diff --git a/library/i18n/locales/hi/connectivity.json b/library/i18n/locales/hi/connectivity.json index dbf1e206f..49202a9be 100644 --- a/library/i18n/locales/hi/connectivity.json +++ b/library/i18n/locales/hi/connectivity.json @@ -54,5 +54,15 @@ "messaging": "मैसेजिंग ऐप" }, "loading": "{name} लोड हो रहा है…" + }, + "adm1": { + "title": "भारत राज्य अनुसार: कभी इंटरनेट का उपयोग किया", + "women": "महिलाएँ", + "men": "पुरुष", + "total": "कुल", + "urban": "शहरी", + "rural": "ग्रामीण", + "source": "NFHS-5 (2019–21), 15–49 वर्ष के लोग: जिन्होंने कभी इंटरनेट का उपयोग किया है उनका प्रतिशत। यह लोगों का सर्वेक्षण है, सब्सक्रिप्शन की गिनती नहीं।", + "missing": "{names} की राज्य सीमा अभी उपलब्ध नहीं है: उनके आँकड़े डेटा में हैं, नक्शे पर नहीं।" } } diff --git a/library/i18n/locales/it/connectivity.json b/library/i18n/locales/it/connectivity.json index 4ae10ba55..e527d6de5 100644 --- a/library/i18n/locales/it/connectivity.json +++ b/library/i18n/locales/it/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Messaggistica" }, "loading": "Caricamento di {name}…" + }, + "adm1": { + "title": "India per Stato: hanno mai usato internet", + "women": "Donne", + "men": "Uomini", + "total": "Totale", + "urban": "Urbano", + "rural": "Rurale", + "source": "NFHS-5 (2019–21), persone di 15–49 anni: quota di chi ha mai usato internet. Un’indagine sulle persone, non un conteggio di abbonamenti.", + "missing": "Ancora nessun confine statale per {names}: i loro dati sono nel dataset, non sulla mappa." } } diff --git a/library/i18n/locales/pt/connectivity.json b/library/i18n/locales/pt/connectivity.json index 43f09d95c..c319ee630 100644 --- a/library/i18n/locales/pt/connectivity.json +++ b/library/i18n/locales/pt/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Mensagens" }, "loading": "A carregar {name}…" + }, + "adm1": { + "title": "Índia por estado: já usaram a internet", + "women": "Mulheres", + "men": "Homens", + "total": "Total", + "urban": "Urbano", + "rural": "Rural", + "source": "NFHS-5 (2019–21), pessoas de 15 a 49 anos: proporção que já usou a internet. Uma pesquisa com pessoas, não uma contagem de assinaturas.", + "missing": "Ainda não há limite estadual para {names}: os números estão nos dados, não no mapa." } } diff --git a/library/i18n/locales/ro/connectivity.json b/library/i18n/locales/ro/connectivity.json index b25fd3206..7fad2d97e 100644 --- a/library/i18n/locales/ro/connectivity.json +++ b/library/i18n/locales/ro/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Aplicații de mesagerie" }, "loading": "Se încarcă {name}…" + }, + "adm1": { + "title": "India pe state: au folosit vreodată internetul", + "women": "Femei", + "men": "Bărbați", + "total": "Total", + "urban": "Urban", + "rural": "Rural", + "source": "NFHS-5 (2019–21), persoane de 15–49 de ani: ponderea celor care au folosit vreodată internetul. Un sondaj despre oameni, nu o numărătoare de abonamente.", + "missing": "Încă nu există limită de stat pentru {names}: cifrele lor sunt în date, nu pe hartă." } } diff --git a/library/i18n/locales/ru/connectivity.json b/library/i18n/locales/ru/connectivity.json index d9e594f8e..aa89b1cec 100644 --- a/library/i18n/locales/ru/connectivity.json +++ b/library/i18n/locales/ru/connectivity.json @@ -54,5 +54,15 @@ "messaging": "Мессенджеры" }, "loading": "Загрузка: {name}…" + }, + "adm1": { + "title": "Индия по штатам: когда-либо пользовались интернетом", + "women": "Женщины", + "men": "Мужчины", + "total": "Всего", + "urban": "Город", + "rural": "Село", + "source": "NFHS-5 (2019–21), люди 15–49 лет: доля тех, кто когда-либо пользовался интернетом. Опрос людей, а не подсчёт подписок.", + "missing": "Для {names} ещё нет границы штата: их данные есть в таблице, но не на карте." } } diff --git a/library/i18n/locales/zh/connectivity.json b/library/i18n/locales/zh/connectivity.json index 396ac58c3..7666f9290 100644 --- a/library/i18n/locales/zh/connectivity.json +++ b/library/i18n/locales/zh/connectivity.json @@ -54,5 +54,15 @@ "messaging": "即时通讯" }, "loading": "正在加载{name}…" + }, + "adm1": { + "title": "印度各邦：曾经使用过互联网", + "women": "女性", + "men": "男性", + "total": "合计", + "urban": "城市", + "rural": "农村", + "source": "NFHS-5（2019–21），15–49 岁人群：曾经使用过互联网的比例。这是对人的调查，而不是订阅数统计。", + "missing": "{names} 尚无邦界：其数据在数据集中，但未显示在地图上。" } } diff --git a/package.json b/package.json index 9c0621745..f4605c812 100644 --- a/package.json +++ b/package.json @@ -202,6 +202,7 @@ "gallery": "node internal/generate-gallery.mjs", "gates:post": "node internal/run-parallel.mjs --label=post -- check:drop check:parse verify check:sri check:public-hygiene check:label-joins check:facet-cascade check:facet-one-field check:heartbeat check:kpi-unit check:composite-reg check:descriptions check:no-abs-paths check:no-codename check:dep-names check:composite-srcs check:embed-targets check:nested-token check:i18n-parity check:tabs-localized check:packets-all check:packet-strings-parity check:zone-census check:share-policy check:library-index check:csv-shape check:capability-citations check:catalog-identity check:no-orphan-gates check:quoted-scripts check:done-evidence check:script-flags check:backlog-status check:capability-exemplars check:packet-fixture check:packet-browser check:provider-switch check:locale-reachable check:url-resolver check:manifest-covers check:one-palette check:pin-dim-slider check:legend-source check:backlog-refs check:clustering-modes check:composite-embed-knobs check:composite-locale-leaks check:linked-vocabulary check:wp-embed check:dashboard-geocoder-provider check:leaf-engine-per-provider check:map-props-unit check:composites-mount check:composite-interop check:no-free-identifiers check:map-fly-reduced-motion check:mst-clustering check:list-prop-unit check:profiles-mount check:cdn-pins check:no-eval check:popup-escaping check:i18n-treeshake check:pinned-umd check:one-palette:self-test", "gates:pre": "node internal/run-parallel.mjs --label=pre -- check:template-literal check:mjs-parse check:sfc-parse check:tab-radius check:synced-css check:doc-scripts", + "internet:adm1": "node plugin-designs/cities-internet/scripts/build-adm1-internet.mjs", "library-index": "node internal/generate-library-index.mjs", "lists": "node library/scripts/people-groups/build-lists.mjs", "packet-fixture": "node internal/generate-packet-fixture.mjs", @@ -360,6 +361,7 @@ "check:zone-census": "every zone a USER CAN SELECT must have a poster (asks the LEGEND, not clusters.json — two collapsed deaf lists are unreachable and not a gap). CONDITIONAL: SKIPs without out/posters/, which is gitignored — run `bun run posters` first. It cannot be fixtured like check:packets-all, because it asserts COVERAGE of real generated output and a fixture would only assert the fixture is complete.", "deploy:dev": "destination + allowlist come from vite.doxa-maps-build-config.json (dropin.dest / dropin.include); DOXA_DROPIN_DEST= overrides the destination", "gallery": "writes public/__gallery/index.html — the ARCHIVED bundle-index gallery, from public/doxa-maps/manifest.json. It is NO LONGER the root page: as of 2026-09-22 `/` mounts in BOTH trees (the built root page is written by `bun run tree`), and the gallery is the opt-in index at /__gallery. Archived, not deleted — the dev server imports renderGallery()/readBuildConfig() from this module.", + "internet:adm1": "regenerate data/tables/internet-by-adm1.json (internet use by first-level area; India from NFHS-5 2019-21, CC BY 4.0) from data/internet/ through a strict name crosswalk to the shipped gb-IND-ADM1 boundaries. Fails on an unmatched name, never guesses. Generic rows (iso3, adm1, measure, sex, area, value, source, year) so other plugins and go-int can reuse it.", "library-index": "regenerate documentation/reference-library-index.md — the DERIVED menu of the 84 reusable library pieces an author can import instead of rebuilding. Was UNREACHABLE, and the index did not exist at all: its header promised 'can't drift from the code' while nothing ever ran it.", "lists": "regenerate data/people-groups/lists/.json, the DOXA slugs in each people-group list of library/lists/lists.json, from the IMB CSV and the DOXA snapshot. Re-run after either changes.", "packet-fixture": "regenerate the committed records subset (smallest zone, image_url stripped) that lets CI build a packet at all — out/ is gitignored, so a clean checkout has neither the records cache nor any packet.", diff --git a/plugin-designs/cities-internet/connectivity-map.vue b/plugin-designs/cities-internet/connectivity-map.vue index ac58c5f00..e2e1f1eec 100644 --- a/plugin-designs/cities-internet/connectivity-map.vue +++ b/plugin-designs/cities-internet/connectivity-map.vue @@ -78,6 +78,10 @@ const rows = ref([]) const selected = ref(null) const aiNoticeOpen = ref(true) // dismissible AI-research disclaimer in the detail sheet const err = ref(null) +// India by state (data/tables/internet-by-adm1.json, NFHS-5): the one country with sub-national data. +const adm1 = shallowRef(null) // { meta, byArea: { [adm1]: { name, women: {total,urban,rural}, men: {…} } } } +const adm1Sex = ref('women') // which half of the survey the fill shows; both are in the sheet +const selectedAdm1 = ref(null) // ── People-group dots (Driver: "red dots on the map to show me where the people groups are") // The DOXA list from pray-tools, the same list Prayer Progress draws. It carries the slug the @@ -264,12 +268,76 @@ function paint(map, adm0) { // A tap on a people-group dot belongs to the dot, not the country under it. if (map.getLayer('ci-pg-dots') && map.queryRenderedFeatures(e.point, { layers: ['ci-pg-dots'] }).length) return const iso = e.features?.[0]?.properties?.iso3 - if (iso && byIso.value[iso]) { uiStore?.selectPeopleGroup(null); selected.value = byIso.value[iso] } + if (iso && byIso.value[iso]) { uiStore?.selectPeopleGroup(null); selectedAdm1.value = null; selected.value = byIso.value[iso] } }) map.on('mouseenter', 'ci-fill', () => { map.getCanvas().style.cursor = 'pointer' }) map.on('mouseleave', 'ci-fill', () => { map.getCanvas().style.cursor = '' }) } +// ── INDIA BY STATE: "ever used the internet", NFHS-5 2019–21, women and men asked separately ───── +// A share of PEOPLE (0–100%), so it gets its own ramp and its own legend block, never the country +// bands: the bands are World Bank national "internet users", a different measure and source. +// Blues, so no state can be read as one of the band colours. +const ADM1_STEPS = [ + { from: 0, color: '#deebf7' }, + { from: 25, color: '#9ecae1' }, + { from: 40, color: '#6baed6' }, + { from: 55, color: '#3182bd' }, + { from: 70, color: '#08519c' }, +] +const adm1Fill = (sex) => ['case', ['==', ['typeof', ['get', sex]], 'number'], + ['step', ['get', sex], ...ADM1_STEPS.flatMap((st, i) => (i === 0 ? [st.color] : [st.from, st.color]))], + 'rgba(0,0,0,0)'] + +async function loadAdm1() { + const [table, geo] = await Promise.all([ + fetch(`${assetsBase.value}/tables/internet-by-adm1.json`).then((r) => { if (!r.ok) throw new Error('internet-by-adm1 ' + r.status); return r.json() }), + fetch(`${assetsBase.value}/boundaries/gb-IND-ADM1.geojson`).then((r) => { if (!r.ok) throw new Error('gb-IND-ADM1 ' + r.status); return r.json() }), + ]) + const byArea = {} + for (const r of table.rows || []) { + if (r.iso3 !== 'IND' || r.measure !== 'ever_used_internet' || !r.adm1) continue + const a = (byArea[r.adm1] ??= { name: r.adm1_name || r.adm1, women: {}, men: {} }) + a[r.sex][r.area] = r.value + } + adm1.value = markRaw({ meta: table.meta || {}, byArea }) + return geo +} + +function paintAdm1(map, geo) { + const byArea = adm1.value.byArea + const fc = { type: 'FeatureCollection', features: (geo.features || []).map((f) => { + const a = byArea[f.properties?.shapeName] + return { type: 'Feature', geometry: f.geometry, + properties: { adm1: f.properties?.shapeName, women: a?.women.total ?? null, men: a?.men.total ?? null } } + }) } + // Under the people-group dots, which stay tappable on top. + const before = map.getLayer('ci-pg-dots') ? 'ci-pg-dots' : undefined + map.addSource('ci-adm1-src', { type: 'geojson', data: fc }) + map.addLayer({ id: 'ci-adm1-fill', type: 'fill', source: 'ci-adm1-src', + paint: { 'fill-color': adm1Fill(adm1Sex.value), 'fill-opacity': 0.85 } }, before) + map.addLayer({ id: 'ci-adm1-line', type: 'line', source: 'ci-adm1-src', + paint: { 'line-color': 'rgba(255,255,255,0.8)', 'line-width': 0.6 } }, before) + // India's national band would sit under its states and show through the two with no geometry + // (Mizoram, Nagaland) as if it were their figure. Take India out of the country layer. + if (map.getLayer('ci-fill')) map.setFilter('ci-fill', ['!=', ['get', 'iso3'], 'IND']) + map.on('click', 'ci-adm1-fill', (e) => { + if (map.getLayer('ci-pg-dots') && map.queryRenderedFeatures(e.point, { layers: ['ci-pg-dots'] }).length) return + const key = e.features?.[0]?.properties?.adm1 + const a = key && byArea[key] + if (a) { uiStore?.selectPeopleGroup(null); selected.value = null; selectedAdm1.value = { key, ...a } } + }) + map.on('mouseenter', 'ci-adm1-fill', () => { map.getCanvas().style.cursor = 'pointer' }) + map.on('mouseleave', 'ci-adm1-fill', () => { map.getCanvas().style.cursor = '' }) +} + +function showAdm1Sex(sex) { + adm1Sex.value = sex + const map = mapRef.value + if (map?.getLayer('ci-adm1-fill')) map.setPaintProperty('ci-adm1-fill', 'fill-color', adm1Fill(sex)) +} +const adm1Missing = computed(() => (adm1.value?.meta?.boundaries?.IND?.missing || []).join(', ')) + // ── HONOUR THE PROVIDER SWITCH: this profile builds its map RAW ───────────── // Every bundle that goes through useMapInstance gets the switch for free. This one calls // `new gl.Map` directly, so it was invisible to it — MEASURED by sweeping all 16 isMap leaves: @@ -293,6 +361,8 @@ onMounted(async () => { try { // The dots are a second layer, not a precondition: if the list fails, the map still shades. const groupsLoaded = loadGroups().catch((e) => { console.warn('[connectivity-map] people groups:', e?.message || e) }) + // India by state is a third layer, and optional like the dots: without it India keeps its band. + const adm1Loaded = loadAdm1().catch((e) => { console.warn('[connectivity-map] India by state:', e?.message || e); return null }) const adm0 = await load() // The pane can unmount during the awaits above (a tab switch mid-load). Building a map // into a container that no longer exists throws; this is the raw-map twin of the @@ -325,6 +395,8 @@ onMounted(async () => { selectedPin.initialize() await groupsLoaded paintGroups(map) + const geo = await adm1Loaded + if (geo && !unmounted) paintAdm1(map, geo) }) } catch (e) { err.value = String(e.message || e) } }) @@ -367,6 +439,16 @@ useShadowStyles( '.gm-key{display:flex;align-items:center;gap:5px;font-size:11px;white-space:nowrap}' + '.gm-sw{width:12px;height:12px;border-radius:3px;flex:none}' + '.gm-caveat{margin-top:5px;font-size:10.5px;opacity:.72;line-height:1.4}' + + '.gm-adm1{margin-top:8px;padding-top:7px;border-top:1px solid rgba(0,0,0,.12)}' + + '.gm-adm1-h{font-weight:600;font-size:12px;margin-bottom:5px}' + + '.gm-seg{display:inline-flex;border:1px solid rgba(0,0,0,.2);border-radius:6px;overflow:hidden;margin-bottom:6px}' + + '.gm-seg button{font:inherit;font-size:11px;padding:3px 10px;border:0;background:transparent;color:inherit;cursor:pointer}' + + '.gm-seg button.on{background:#08519c;color:#fff}' + + '.gm-adm1-t{width:100%;border-collapse:collapse;font-size:12px;margin:4px 0 6px}' + + '.gm-adm1-t th,.gm-adm1-t td{padding:3px 4px;text-align:end}' + + '.gm-adm1-t th:first-child{text-align:start}' + + '.is-dark .gm-adm1{border-top-color:rgba(255,255,255,.15)}' + + '.is-dark .gm-seg{border-color:rgba(255,255,255,.3)}' + // DETAIL: a bottom sheet on a phone, a corner card on desktop. '.gm-sheet{position:absolute;left:0;right:0;bottom:0;z-index:6;max-height:62%;overflow-y:auto;' + 'background:#fff;color:#0f1419;border-radius:14px 14px 0 0;padding:14px 16px 22px;' + @@ -426,6 +508,21 @@ useShadowStyles(
{{ t('connectivity.caveat') }}
+ +
+
{{ t('connectivity.adm1.title') }}
+
+ + +
+
+ + {{ i + 1 < ADM1_STEPS.length ? st.from + '–' + ADM1_STEPS[i + 1].from + '%' : st.from + '%+' }} + +
+
{{ t('connectivity.adm1.source') }}
+
{{ t('connectivity.adm1.missing', { names: adm1Missing }) }}
+
{{ err }}
@@ -438,6 +535,25 @@ useShadowStyles( + +
+
+ {{ selectedAdm1.name }} + +
+
{{ t('connectivity.adm1.title') }}
+ + + + + + + + +
{{ t('connectivity.adm1.total') }}{{ t('connectivity.adm1.urban') }}{{ t('connectivity.adm1.rural') }}
{{ t('connectivity.adm1.' + sex) }}{{ selectedAdm1[sex][area] != null ? selectedAdm1[sex][area] + '%' : '—' }}
+

{{ t('connectivity.adm1.source') }}

+
+
diff --git a/plugin-designs/cities-internet/scripts/build-adm1-internet.mjs b/plugin-designs/cities-internet/scripts/build-adm1-internet.mjs new file mode 100644 index 000000000..309802b1b --- /dev/null +++ b/plugin-designs/cities-internet/scripts/build-adm1-internet.mjs @@ -0,0 +1,118 @@ +#!/usr/bin/env node +/** + * build-adm1-internet.mjs — internet use by first-level administrative area (ADM1), from data. + * + * node plugin-designs/cities-internet/scripts/build-adm1-internet.mjs + * + * READS data/internet/nfhs5-internet-by-state.csv India, NFHS-5 2019–21 (see data/internet/README.md) + * data/internet/adm1-crosswalk-IND.json source names -> boundary shapeName (strict) + * plugin-designs/my-upg-100-list/data/gb-IND-ADM1.geojson the boundary file the map draws + * WRITES data/tables/internet-by-adm1.json served as assets/tables/internet-by-adm1.json + * + * THE TABLE IS GENERIC ON PURPOSE (other plugins and go-int reuse it). One row per + * (iso3, adm1, measure, sex, area): no India-specific shape, so a second country or a second + * measure is more rows, not a new format. `meta.boundaries[iso3]` names the geometry file and the + * property its `adm1` joins on; `meta.measures` and `meta.sources` say what each number is. + * + * STRICT. The run FAILS when a source name is missing from the crosswalk, when a crosswalk target + * is not a shapeName in the boundary file, or when a value is not a number in 0–100. A name is + * never guessed. Source rows that have no geometry (crosswalk `adm1: null`) are KEPT, keyed by + * their source name, and listed in meta.boundaries[iso3].missing, so nothing is silently dropped. + */ +import { readFileSync, writeFileSync } from 'node:fs' +import { resolve, dirname, join } from 'node:path' +import { fileURLToPath } from 'node:url' + +const ROOT = resolve(dirname(fileURLToPath(import.meta.url)), '../../..') +const CSV = join(ROOT, 'data/internet/nfhs5-internet-by-state.csv') +const CROSSWALK = join(ROOT, 'data/internet/adm1-crosswalk-IND.json') +const BOUNDARY = join(ROOT, 'plugin-designs/my-upg-100-list/data/gb-IND-ADM1.geojson') +const OUT = join(ROOT, 'data/tables/internet-by-adm1.json') + +const fail = (msg) => { console.error('build-adm1-internet: FAIL — ' + msg); process.exit(1) } + +// A quoted-field CSV reader (the NFHS file quotes names that contain commas). +function parseCsv(text) { + const rows = []; let row = []; let f = ''; let q = false + for (let i = 0; i < text.length; i++) { + const c = text[i] + if (q) { if (c === '"') { if (text[i + 1] === '"') { f += '"'; i++ } else q = false } else f += c } + else if (c === '"') q = true + else if (c === ',') { row.push(f); f = '' } + else if (c === '\n') { row.push(f); rows.push(row); row = []; f = '' } + else if (c !== '\r') f += c + } + if (f || row.length) { row.push(f); rows.push(row) } + const head = rows.shift() + return rows.filter((r) => r.length === head.length).map((r) => Object.fromEntries(head.map((h, i) => [h, r[i]]))) +} + +const src = parseCsv(readFileSync(CSV, 'utf8')) +const crosswalk = JSON.parse(readFileSync(CROSSWALK, 'utf8')).map +const shapeNames = new Set(JSON.parse(readFileSync(BOUNDARY, 'utf8')).features.map((f) => f.properties.shapeName)) + +const SEX = { 'Women who have ever used the internet (%)': 'women', 'Men who have ever used the internet (%)': 'men' } +const AREAS = { total: 'nfhs5_total', urban: 'nfhs5_urban', rural: 'nfhs5_rural' } + +const rows = [] +const national = [] +const missing = new Set() +for (const r of src) { + const sex = SEX[r.indicator.replace(/^\d+\.\s*/, '')] + if (!sex) fail(`unexpected indicator "${r.indicator}"`) + const cw = crosswalk[r.state] + if (!cw) fail(`"${r.state}" is not in data/internet/adm1-crosswalk-IND.json`) + if (cw.adm1 && !shapeNames.has(cw.adm1)) fail(`crosswalk maps "${r.state}" to "${cw.adm1}", which is not a shapeName in gb-IND-ADM1.geojson`) + if (!cw.adm1 && !cw.reason) fail(`crosswalk entry for "${r.state}" has no adm1 and no reason`) + for (const [area, col] of Object.entries(AREAS)) { + const raw = String(r[col] ?? '').trim() + if (raw === '' || raw === '*' || raw === 'na') continue // not reported for this cell + const value = Number(raw) + if (!Number.isFinite(value) || value < 0 || value > 100) fail(`"${r.state}" ${sex} ${area}: "${raw}" is not a share in 0–100`) + const row = { iso3: 'IND', measure: 'ever_used_internet', sex, area, value, source: 'nfhs5', year: '2019-21' } + if (cw.national) { national.push(row); continue } + if (!cw.adm1) missing.add(r.state) + rows.push({ ...row, adm1: cw.adm1 || null, adm1_name: r.state }) + } +} +if (!rows.length) fail('no rows (vacuous run)') + +const out = { + meta: { + title: 'Internet use by first-level administrative area', + grain: 'one row per iso3 x adm1 x measure x sex x area', + measures: { + ever_used_internet: { + label: 'Ever used the internet', + unit: '%', + population: 'people aged 15–49, women and men asked separately', + note: 'A survey SHARE OF PEOPLE (0–100). Not a subscription count: never put it on one scale with subscriptions per 100.', + }, + }, + sources: { + nfhs5: { + name: 'National Family Health Survey 5 (NFHS-5), IIPS / Ministry of Health and Family Welfare, India', + year: '2019-21', + url: 'http://rchiips.org/nfhs/', + via: 'https://github.com/pratapvardhan/NFHS-5 (CSV transcription of the state fact sheets)', + licence: 'CC BY 4.0', + attribution: 'NFHS-5 (IIPS/MoHFW) state fact sheets, via pratapvardhan/NFHS-5 (CC BY 4.0)', + }, + }, + boundaries: { + IND: { + file: 'boundaries/gb-IND-ADM1.geojson', + key: 'shapeName', + licence: 'geoBoundaries gbOpen, India ADM1: CC BY 2.5 IN (datameet)', + missing: [...missing].sort(), + missing_reason: 'no geometry in the shipped boundary file (the UPG-100 partition: 34 of 36 units)', + }, + }, + national, + generated_by: 'plugin-designs/cities-internet/scripts/build-adm1-internet.mjs', + }, + rows, +} +writeFileSync(OUT, JSON.stringify(out, null, 1) + '\n') +const drawn = new Set(rows.filter((r) => r.adm1).map((r) => r.adm1)).size +console.log(`build-adm1-internet: ${rows.length} rows · IND ${drawn} ADM1 areas drawn · ${missing.size} without geometry (${[...missing].join(', ') || 'none'}) · national ${national.length} rows`)