Designing surveys require relevant datasets to be used as basis for sample size calculations, sampling design, survey planning/logistics and survey implementation. These include datasets on population, lists of sampling clusters, map datasets for spatial sampling, and previous survey datasets that can be used for estimating indicator variance and design effects. This package contains relevant datasets for use in designing surveys in Tanzania.
The development version of the tanzania package can be installed from
GitHub with:
if(!require(remotes)) install.packages("remotes")
remotes::install_github("spatialworks/tanzania")When installing tanzania, geospatial packages on which tanzania
depends on are also installed. To use tanzania package, it will be
important to load these package dependencies that have been installed.
This can be done by:
library(rgdal)
library(rgeos)
library(raster)The Tanzania region borders is accessed via the region dataset.
tanzania::region
#> class : SpatialPolygonsDataFrame
#> features : 30
#> extent : 29.38074, 40.44564, -11.76401, -0.9857875 (xmin, xmax, ymin, ymax)
#> crs : +proj=longlat +datum=WGS84 +no_defs
#> variables : 2
#> names : Region_Cod, Region_Nam
#> min values : 01, Arusha
#> max values : 55, TangaThe region borders of Tanzania can be plotted by:
sp::plot(tanzania::region)
The Tanzania district borders is accessed via the district dataset.
tanzania::district
#> class : SpatialPolygonsDataFrame
#> features : 195
#> extent : 29.59019, 40.44564, -11.76401, -0.9857875 (xmin, xmax, ymin, ymax)
#> crs : +proj=longlat +datum=WGS84 +no_defs
#> variables : 4
#> names : Region_Nam, Region_Cod, District_C, NewDist20
#> min values : Arusha, 1, 1, Arusha DC
#> max values : Tanga, 55, 11, WeteThe district borders of Tanzania can be plotted by:
sp::plot(tanzania::district)
The Tanzania ward borders is accessed via the ward dataset.
tanzania::ward
#> class : SpatialPolygonsDataFrame
#> features : 3644
#> extent : 29.59019, 40.44564, -11.76401, -0.9857875 (xmin, xmax, ymin, ymax)
#> crs : +proj=longlat +datum=WGS84 +no_defs
#> variables : 9
#> names : Region_Cod, Region_Nam, District_C, District_N, Ward_Code, Ward_Name, Division, SHAPE_Leng, SHAPE_Area
#> min values : 01, Arusha, 01, Arusha, 011, Aghondi, Amani, 0.0103364558854, 5.9905934117e-06
#> max values : 55, Tanga, 10, Wete, 452, Zuzu, Ziwani, 6.39559993421, 0.928253270256The ward borders of Tanzania can be plotted by:
sp::plot(tanzania::ward)
The Tanzania village borders is accessed via the village dataset.
tanzania::village
#> class : SpatialPolygonsDataFrame
#> features : 18421
#> extent : 29.5939, 40.44502, -11.74633, -0.990231 (xmin, xmax, ymin, ymax)
#> crs : +proj=longlat +a=6378249.145 +rf=293.465006079117 +no_defs +type=crs
#> variables : 45
#> names : REG_CODE, REGNAME, DIST_CODE, DISTNAME, WARD_CODE, WARD_NAME, STREET, MALE, FEMALE, TOTAL, NUMBER, AVERAGE, SINGLE, MARIED, UNKNOWN, ...
#> min values : 01, Arusha, 01, Arumeru, 011, Aghondi, ??, 0, 0, 0, 0, 0, 0, 0, 0, ...
#> max values : 55, Tanga, 08, Wete, 481, Zuzu, Zuzu - Soweto, 41574, 43101, 84675, 84675, 544.5, 57386, 21310, 5979, ...The village borders of Tanzania can be plotted by:
sp::plot(tanzania::village)
The Tanzania livelihood zone borders is accessed via the
livelihood_zone dataset.
tanzania::livelihood_zone
#> class : SpatialPolygonsDataFrame
#> features : 80
#> extent : 29.32717, 40.44556, -11.76007, -0.990736 (xmin, xmax, ymin, ymax)
#> crs : +proj=longlat +datum=WGS84 +no_defs
#> variables : 15
#> names : OBJECTID, FNID, EFF_YEAR, COUNTRY, LZNUM, LZCODE, LZNAMEEN, LZNAMEFR, LZNAMESP, LZNAMEPT, CLASS, LZSZCODE, LZTYPE, MAINCROPS, MAINLSTOCK
#> min values : 0, TZ2009L101, 2009, TZ, 1, TZ01, Babati Kwaraa Maize, Beans, Sunflower, and Coffee, NA, NA, NA, NA, NA, NA, NA, NA
#> max values : 0, TZ2009L199, 2009, TZ, 99, TZ99, Western Lakeshore Coffee, Fishing, and Banana, NA, NA, NA, NA, NA, NA, NA, NAThe livelihood zone borders of Tanzania can be plotted by:
sp::plot(tanzania::livelihood_zone)