| Title: | 2021 Ghana Population and Housing Census Results as Data Frames |
| Version: | 0.1.0 |
| Description: | Datasets from the 2021 Ghana Population and Housing Census Results. Users can access results as 'tidyverse' and 'sf'-Ready Data Frames. The data in this package is scraped from pdf reports released by the Ghana Statistical Service website https://census2021.statsghana.gov.gh/ . The package currently only contains datasets from the literacy and education reports. Namely, school attendance data for respondents aged 3 years and above. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.2 |
| Maintainer: | Ama Owusu-Darko <aowusuda@asu.edu> |
| Depends: | R (≥ 3.5.0) |
| LazyData: | true |
| Suggests: | dplyr, knitr, magrittr, rmarkdown, sf, tmap |
| VignetteBuilder: | knitr |
| URL: | https://github.com/ktemadarko/rGhanaCensus |
| BugReports: | https://github.com/ktemadarko/rGhanaCensus/issues |
| NeedsCompilation: | no |
| Packaged: | 2022-01-13 11:01:36 UTC; LENOVO |
| Author: | Ama Owusu-Darko [cre, aut] |
| Repository: | CRAN |
| Date/Publication: | 2022-01-13 20:02:43 UTC |
Ghana School Attendance Indicator data
Description
The Ghana_2021_school_attendance dataset contains school attendance indicators for respondents in the 16 regions of Ghana surveyed in the 2021 Ghana Population and Housing Census.
Details -Age range of survey respondents in this data set 3 years and above.
Usage
Ghana_2021_school_attendance
Format
A data frame with 64 rows and 10 variables:
Region
A factor with 16 levels with the names of the regions in Ghana
Gender
A factor with 2 levels
Locality
A factor with 2 levels describing with the respondents surveyed lived in an urban or rural area
Currently_Attending_School
numeric column with the raw count values of survey respondents aged 3 years and above currently attending school
Percent_Currently_Attending_School
A numeric column with the derived percentage of
((Currently_Attending_School)/Sum_of_Respondents_(3_years_and_above))*100 to two decimal places
Never_Attended_School
-A numeric column with the raw count values of survey respondents aged 3 years and above who have never attended school
Percent_Never_Attended_School
A numeric column with the derived percentage of
((Never_Attended_School)/Sum_of_Respondents_(3_years_and_above))*100 to two decimal places
Dropped_out_of_School
A numeric column with the raw count values of survey respondents aged 3 years and above who were in school but dropped out
Percent_Dropped_out_of_School
A numeric column with the derived percentage of
((Dropped_out_of_School)/Sum_of_Respondents_(3_years_and_above))*100 to two decimal places
Sum_of_Respondents_(3_years_and_above)
A numeric column with the raw sum values in each row.
That is sum of (Currently_Attending_School, Never_Attended_School, Dropped_out_of_School) in each row
Source
School attendance data
Scraped from Ghana Statistical Service published 2021 Ghana Population and Housing Census Results Volume 3D Literacy and Education PDF Reports
Ghana regional administrative boundaries geometry data
Downloaded from Humanitarian data exchange website on 7th January, 2022
https://data.humdata.org/dataset/ghana-administrative-boundaries
Ghana School Attendance Indicator data plus geometry
Description
The Ghana_2021_school_attendance_geometry dataset contains school attendance indicators for respondents in the 16 regions of Ghana surveyed in the 2021 Ghana Population and Housing Census plus Ghana regional administrative boundaries.
Details Age range of survey respondents in this data set 3 years and above.
Usage
Ghana_2021_school_attendance_geometry
Format
A data frame with 64 rows and 10 variables:
Region
A factor with 16 levels with the names of the regions in Ghana
Gender
A factor with 2 levels
Locality
A factor with 2 levels describing with the respondents surveyed lived in an urban or rural area
Currently_Attending_School
numeric column with the raw count values of survey respondents aged 3 years and above currently attending school
Percent_Currently_Attending_School
A numeric column with the derived percentage of
((Currently_Attending_School)/Sum_of_Respondents_(3_years_and_above))*100 to two decimal places
Never_Attended_School
-A numeric column with the raw count values of survey respondents aged 3 years and above who have never attended school
Percent_Never_Attended_School
A numeric column with the derived percentage of
((Never_Attended_School)/Sum_of_Respondents_(3_years_and_above))*100 to two decimal places
Dropped_out_of_School
A numeric column with the raw count values of survey respondents aged 3 years and above who were in school but dropped out
Percent_Dropped_out_of_School
A numeric column with the derived percentage of
((Dropped_out_of_School)/Sum_of_Respondents_(3_years_and_above))*100 to two decimal places
Sum_of_Respondents_(3_years_and_above)
A numeric column with the raw sum values in each row.
That is sum of (Currently_Attending_School, Never_Attended_School, Dropped_out_of_School) in each row
Source
School attendance data
Scraped from Ghana Statistical Service published 2021 Ghana Population and Housing Census Results Volume 3D Literacy and Education PDF Reports
Ghana regional administrative boundaries geometry data
Downloaded from Humanitarian data exchange website on 7th January, 2022
https://data.humdata.org/dataset/ghana-administrative-boundaries
Examples
## Not run:
#Example
#Create a interactive map with the package tmap that displays the
#regional distribution of percentage of students 3 years or older who have dropped out of school.
#Load required packages
library(sf)
library(tmap)
library(dplyr)
library(magrittr)
#Load geometry data
data("Ghana_2021_school_attendance_geometry", package = "rGhanaCensus")
#Convert to sf data frame and assign a name
#In this example, "Ghana_edu_sf" will be the name of the sf data frame created.
Ghana_edu_sf<- sf::st_as_sf(Ghana_2021_school_attendance_geometry)
#Use tmap to create interactive map
tmap_mode("plot")
Ghana_edu_sf %>%
dplyr::filter(Locality=="Urban") %>%
tm_shape()+
tm_polygons(id="Region", col="Percent_Dropped_out_of_School")+
tm_text(text="Percent_Dropped_out_of_School")+
tm_facets(by="Gender")
## End(Not run)