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An R package on Nigeria and for Nigeria
The goal of naijR is to make it easier for R users to work with data related to Nigeria.
One of the useful aspects of this package is enabling users to plot country and sub-national geo-spatial maps. Currently, only vector-type graphics are supported. To find out more, read the vignette–accessible from within R as follows:
vignette('nigeria-maps', 'naijR')To create a list of all the States of the Nigerian Federation, simply
call states().
library(naijR, quietly = TRUE)
ss <- states()
head(ss)
States
------
- Abia
- Adamawa
- Akwa Ibom
- Anambra
- Bauchi
- Bayelsa
cat(sprintf("\n...but Nigeria has %i States.", length(ss)))
...but Nigeria has 37 States.States from a given geo-political zone can also be selected:
states(gpz = "ne") # i.e. North-East
States
------
- Adamawa
- Bauchi
- Borno
- Gombe
- Taraba
- Yobe For other capabilities of this function, see
?states().
This is a basic example that shows how to very quickly fetch the names of Local Government Areas within a given State:
lgas("Imo")
LGAs
----
- Aboh Mbaise
- Ahiazu Mbaise
- Ehime Mbano
- Ihitte/Uboma
- Ideato North
- Ideato South
- Ezinihitte-Mbaise
- Isu
- Oguta
- Obowo
- Nwangele
- Njaba
- Ngor Okpala
- Mbaitoli
- Nkwerre
- Orsu
- Orlu
- Onuimo
- Okigwe
- Ohaji/Egbema
- Oru East
- Isiala Mbano
- Ikeduru
- Owerri Municipal
- Owerri West
- Owerri North
- Oru West To list all the LGAs in Nigeria, call the same function without any parameters:
n <- length(lgas())
sprintf("Nigeria has a total of %i Local Government Areas", n)
[1] "Nigeria has a total of 774 Local Government Areas"Want to create a function to check how many LGAs a particular State has?
how_many_lgas <- function(state) {
n <- length(lgas(state))
cat(state, "State has", n, "LGAs\n")
}
how_many_lgas("Sokoto")
Sokoto State has 23 LGAsIt is common to come across datasets where phone numbers are wrongly
entered or misinterpreted by software like MS Excel. The function
fix_mobile() helps with this.
fix_mobile("8032000000")
[1] "08032000000"The function works on vectors; thus an entire column of a table with phone numbers can be quickly processed. Illegible or irreparable numbers are turned into missing values, e.g.
(dat <- data.frame(
serialno = 1:8,
phone = c(
"123456789",
"0123456789",
"8000000001",
"9012345678",
"07098765432",
"08123456789",
"09064321987",
"O8055577889"
)
))
serialno phone
1 1 123456789
2 2 0123456789
3 3 8000000001
4 4 9012345678
5 5 07098765432
6 6 08123456789
7 7 09064321987
8 8 O8055577889fix_mobile(dat$phone)
[1] NA NA "08000000001" "09012345678" "07098765432"
[6] "08123456789" "09064321987" "08055577889"To download and install the current stable version of this package from CRAN:
install.packages("naijR")The development version can be obtained from GitHub with:
# install.packages("pak") # if necessary
pak::pkg_install("ropensci/naijR")Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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