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.
This is a package for use in the R ecosystem. To install R, visit https://cran.r-project.org.
To download and install the current stable version of this package from CRAN:
The development version can be obtained from GitHub with:
A major feature of this version of the packages is the introduction of various map drawing capabilities. To read more about this, read the vignette with this
To create a list of all the States of the Nigerian Federation, simply call states()
library(naijR, quietly = TRUE)
states()
#> [1] "Abia" "Adamawa"
#> [3] "Akwa Ibom" "Anambra"
#> [5] "Bauchi" "Bayelsa"
#> [7] "Benue" "Borno"
#> [9] "Cross River" "Delta"
#> [11] "Ebonyi" "Edo"
#> [13] "Ekiti" "Enugu"
#> [15] "Federal Capital Territory" "Gombe"
#> [17] "Imo" "Jigawa"
#> [19] "Kaduna" "Kano"
#> [21] "Katsina" "Kebbi"
#> [23] "Kogi" "Kwara"
#> [25] "Lagos" "Nasarawa"
#> [27] "Niger" "Ogun"
#> [29] "Ondo" "Osun"
#> [31] "Oyo" "Plateau"
#> [33] "Rivers" "Sokoto"
#> [35] "Taraba" "Yobe"
#> [37] "Zamfara"
States from a given geo-political zone can also be selected
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_ng("Imo")
#> [1] "Aboh Mbaise" "Ahiazu Mbaise" "Ehime Mbano" "Ezinihitte"
#> [5] "Ideato North" "Ideato South" "Ihitte/Uboma" "Ikeduru"
#> [9] "Isiala Mbano" "Isu" "Mbaitoli" "Ngor Okpala"
#> [13] "Njaba" "Nkwerre" "Nwangele" "Obowo"
#> [17] "Oguta" "Ohaji/Egbema" "Okigwe" "Orlu"
#> [21] "Orsu" "Oru East" "Oru West" "Owerri Municipal"
#> [25] "Owerri North" "Owerri West" "Unuimo"
To list all the LGAs in Nigeria, call the same function without any parameters:
n <- length(lgas_ng())
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(naijR::lgas_ng(state))
cat(state, "State has", n, "LGAs\n")
}
how_many_lgas("Sokoto")
#> Sokoto State has 23 LGAs
how_many_lgas("Ekiti")
#> Ekiti State has 16 LGAs
It 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.
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 O8055577889
fix_mobile(dat$phone)
#> [1] NA NA "08000000001" "09012345678" "07098765432"
#> [6] "08123456789" "09064321987" NA
Some enhancements to expect in future updates:
0
).fix_mobile()
currently works with character vectors. It will be allowed to work with numeric vectors, converting these to character vectors internally.This is an open source project and contributions are welcome. Pull requests for R code or documentation, and any suggestions for making this effort worthwhile will be gladly entertained.
For bug reports or feature requests, kindly submit an issue.