A synthetic business establishment frame inspired by World Bank Enterprise Surveys. Uses real Nigeria states and geopolitical zones but contains entirely fictional data.
nigeria_businessA tibble with approximately 10,000 rows and 7 columns:
Character. Unique business identifier
Factor. Geopolitical zone (North Central, North East, North West, South East, South South, South West)
Factor. State name (36 states + FCT)
Factor. Business sector (Manufacturing, Retail Trade, Wholesale Trade, Services, Construction, Transport, Hospitality)
Factor. Size classification (Micro: 1-4, Small: 5-19, Medium: 20-99, Large: 100+)
Integer. Number of employees (measure of size)
Numeric. Annual turnover in Naira
This dataset is designed for demonstrating:
Business/enterprise surveys
Stratification by sector and size class
PPS sampling using employment
Geographic stratification by zone/state
The distribution reflects typical business demographics with majority micro/small enterprises, concentrated in South West (especially Lagos).
This is a synthetic dataset. States and zones are real but all data values are fictional.
data(nigeria_business)
head(nigeria_business)
#> # A tibble: 6 × 7
#> enterprise_id zone state sector size_class employees annual_turnover
#> <chr> <fct> <fct> <fct> <fct> <dbl> <dbl>
#> 1 NG_No_Ben_00001 North Centr… Benue Servi… Micro 3 2800000
#> 2 NG_No_Ben_00002 North Centr… Benue Retai… Small 14 54969000
#> 3 NG_No_Ben_00003 North Centr… Benue Retai… Micro 3 6254000
#> 4 NG_No_Ben_00004 North Centr… Benue Retai… Large 609 2744346000
#> 5 NG_No_Ben_00005 North Centr… Benue Const… Micro 3 3627000
#> 6 NG_No_Ben_00006 North Centr… Benue Retai… Medium 37 138776000
table(nigeria_business$size_class)
#>
#> Micro Small Medium Large
#> 5935 3017 1336 543
# Stratified sample by sector and size
if (FALSE) { # \dontrun{
sampling_design() |>
stratify_by(sector, size_class) |>
draw(n = 5, method = "pps_brewer", mos = employees) |>
execute(nigeria_business, seed = 42)
} # }