Sample dataset of households

This is a synthetic dataset containing household information primarily used for demonstration purposes on how to use the mpindex package.

Usage

df_household

Format

A tibble with 198 rows and 21 variables:

uuid

Unique ID

class

Urbanity: Rural or Urban

drinking_water

Acess to drinking water: 1 - improved; 2 - unimproved

toilet

Service level of toilet or sanitation facility: 1 - basic; 2 - limited; 3 - unimproved; 4 - open defecation

with_child_died

With at least one (1) child died in the last five (5) years: 1 - with child died; 2 - without child died

roof

Main construction material of the roof: 1 - galvanized iron/aluminum; 2 - concrete/clay tile; 3 - half galvanized iron and half concrete; 4 - wood/bamboo; 5 - cogon/nipa/anahaw; 6 - asbestos; 7 - makeshift/salvaged/improvised materials; 9 - other construction material

walls

Main construction material of the outer walls: 1 - concrete/brick/stone; 2 - wood; 3 - half concrete/brick/stone and half wood; 4 - Galvanized iron/aluminum; 5 - bamboo/sawali/cogon/nipa; 6 - asbestos; 7 - glass; 8 - makeshift/salvaged/improvised materials; 9 - none; 10 - concrete hollow blocks; 11 - concrete hollow blocks/wood; 12 - shear walls; 99 - other construction material

floor

Main construction material of the floor: 1 - concrete; 2 - wood; 3 - coconut lumber; 4 - bamboo; 5 - earth/sand/mud; 6 - makeshift/salvaged/improvised materials; 9 - other construction material

electricity

Access to electricity: 1 - with access to electricity; 2 - without access to electricity

cooking_fuel

Fuel use for cooking: 1 - electricity; 2 - kerosene (gaas); 3 - liquified petroleum gas (LPG); 4 - charcoal; 5 - wood; 6 - none; 9 - other cooking fuel such as dung, agricultural crop, or shrubs

asset_radio

Number of working radio owned by the household

asset_tv

Number of working television owned by the household

asset_telephone

Number of working telephone owned by the household

asset_mobile_phone

Number of working mobile phone owned by the household

asset_computer

Number of working computer owned by the household

asset_animal_cart

Number of animal carts owned by the household

asset_bicycle

Number of bicycle owned by the household

asset_motorcycle

Number of motorcylce owned by the household

asset_refrigerator

Number of working refrigerator owned by the household

asset_car

Number of car owned by the household

asset_truck

Number of trucks owned by the household

See also

df_household_roster

Examples

df_household
#> # A tibble: 198 × 21
#>    uuid            class drinking_water toilet with_child_died  roof walls floor
#>    <chr>           <chr>          <int>  <int>           <int> <int> <int> <int>
#>  1 5dbec60a-ebda-… Rural              1      1               2     1     1     1
#>  2 8b70c208-8642-… Rural              1      1               2     1     1     1
#>  3 aa7cb64d-ba16-… Rural              1      1               2     1     3     1
#>  4 df3e5c9b-7218-… Rural              1      1               2     1     3     1
#>  5 57babe6a-c163-… Rural              1      1               2     1     3     1
#>  6 ba3f75cd-102d-… Rural              1      1               2     1     5     4
#>  7 291c03d9-7947-… Rural              1      1               2     1     5     1
#>  8 b8d1b52e-2b5d-… Rural              1      1               2     1     1     1
#>  9 2e80bf1a-03e9-… Rural              1      1               2     1     3     1
#> 10 208992f0-9c6d-… Rural              1      1               2     1     1     1
#> # ℹ 188 more rows
#> # ℹ 13 more variables: electricity <int>, cooking_fuel <int>,
#> #   asset_refrigerator <int>, asset_radio <int>, asset_tv <int>,
#> #   asset_telephone <int>, asset_mobile_phone <int>, asset_animal_cart <int>,
#> #   asset_computer <int>, asset_motorcycle <int>, asset_bicycle <int>,
#> #   asset_car <int>, asset_truck <int>