README.md

In BroVic/naijR: Operations to Ease Data Analyses Specific to Nigeria

naijR

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.

Usage

Some simple operations

Maps

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')

Administrative Regions

States

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().

Local Government Areas

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 LGAs

Working with phone numbers

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.

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 O8055577889

fix_mobile(dat$phone)
[1] NA            NA            "08000000001" "09012345678" "07098765432"
[6] "08123456789" "09064321987" "08055577889"

Installation

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("remotes")
remotes::install_github("BroVic/naijR",
                        dependencies = TRUE,
                        build_vignettes = TRUE)

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.

BroVic/naijR documentation built on Jan. 31, 2024, 12:02 a.m.