MedDhia/rgph2014tn

Tunisia 2014 Census (RGPH) — R data package # rgph2014tn **Delegation-level data from Tunisia's 2014 General Census of Population and Housing** (*Recensement Général de la Population et de l'Habitat*), published by the Institut National de la Statistique (INS). 169 variables · 264 délégations · 24 gouvernorats · 28 disaggregated data sheets --- ## What's in the data? The package ships a pre-merged master dataset (`rgph_master`) covering all 264 delegations, plus 28 disaggregated sheets broken down by sex and milieu (urban/rural). | Domain | Variables | Examples | |---|---|---| | Demography | 15 | Population, age structure, marital status | | Education | 10 | Enrollment, literacy, attainment, internet use | | Employment | 36 | Unemployment rate, sectoral composition, graduate unemployment | | Migration | 19 | International and internal flows, motives | | Household | 31 | Water, energy, tenure, equipment, communications | | Housing | 29 | Type, size, occupancy, infrastructure, facilities | | Services | 24 | Distance to schools, health centres, sports facilities | | Geography | 3 | Governorate, delegation (Arabic & French) | **Disaggregated sheets** provide breakdowns by sex (male/female/total) and milieu (communal/non-communal/total) at multiple geographic levels, with up to 2,172 rows per sheet. ## Installation ```r # From GitHub: # install.packages("remotes") remotes::install_github("MedDhia/rgph2014tn") ``` ## Quick start ```r library(rgph2014tn) # The master dataset loads lazily data(rgph_master) dim(rgph_master) #> [1] 264 169 # Explore variable definitions cb [1] "master_merged" "demo1" "demo2" "educ1" "educ2" ... # Load a sheet disaggregated by sex and milieu demo [1] 2172 14 ``` ## Example: regional inequality ```r # Unemployment by governorate gov_unemp [1] 0.56 # Simple regression fit <- lm(pct_scolarisation_6_14 ~ pct_eau_potable_sonede, data = rgph_master) summary(fit) ``` ## Data details **Master dataset:** `rgph_master` — 264 rows (one per délégation) × 169 columns. …