A new version of this R package has been released on CRAN, the Comprehensive R Archive Network. It introduces a number of updates that will be described in somewhat detail in this blog post. For a synopsis, read the release notes.
New methods
Methods for some common generic R functions were included in the update. Some of these include c(), [, [[, na.exclude, to mention a few. This confers consistent behaviour to some of the **naijR** objects. For example, when concatenating 2 objects that represent the Nigerian States, we have the following:
library(naijR)
s1 <- states("Imo")
s2 <- states(c("Abia", "Anambra"))
s3 <- c(s1, s2)
s3
## States
## ------
## * Imo
## * Abia
## * Anambra
Similarly, when indexing, the output formatting is retained:
s3[1]
## States
## ------
## * Imo
Other methods added are as follows:
head.regionstail.regionsprint.regionsna.exclude.regionsna.omit.regions
Mobile numbers
The function fix_mobile can now repair phone numbers where zeros (0) are mistakenly replaced with the letter O (whether upper or lower case). As an example:
nums <- c("8034510441", "070304", "09O14358956")
# nums[3] has a letter 'O' in it and is fixed by the function
fix_mobile(nums)
[1] "08034510441" NA "09014358956"
Map legends
Changes were made to the arguments that control how legends are displayed in the maps, particularly choropleths. The way the argument legend.text works is similar to that of the barplot function (from the **graphics** package). Only when this argument is TRUE will the legend be plotted. Also, other arguments that were used for fine-tuning were deprecated – leg.x, leg.y, and leg.orient. Going forward, any low-level legend manipulations should be done with graphics::legend().
As an example, let us create a 2-column data frame with hypothetical data on the
# Create a factor
set.seed(12)
x <- states() |>
length() |>
rnorm(100, 10) |>
round() |>
sample() |>
cut(
breaks = c(80, 89, 99, 109, 119, 129),
labels = c("80-89", "90-99", "100-109", "110-119", "120+"),
include.lowest = TRUE
)
# Make a 2-column data frame and take a look at it
df <- data.frame(state = states(), x)
head(df)
This gives the following output:
## state x
## 1 Abia 90-99
## 2 Adamawa 90-99
## 3 Akwa Ibom 120+
## 4 Anambra 100-109
## 5 Bauchi 90-99
## 6 Bayelsa 90-99
Now, we will use this data frame to create a choropleth map. One of the improvements in this version is that the function map_ng(), when given a two-column data frame will inspect each column, and if one column has valid States or LGAs and the other is a factor, it will automatically create the choropleth visualization. So using our data frame df,
map_ng(data = df)
With the new control given in the current version, we can do away with the legend.
# note partial matching with argument 'legend.text'
map_ng(data = df, legend = FALSE)
Due to the shape of the map, the best place to place any legend is in the bottom right corner. However, if the user wants to place it elsewhere, we can now use the Base R plotting constructs to do fine-grained touch-ups. This, of course, is for users who are more comfortable coding in R. As an example,
# Create objects containing the factor levels and then the colours
# map_ng() uses RColorBrewer internally, so we are using this
# to manually define the colours for the legend itself
categories <- levels(df$x)
colors <- RColorBrewer::brewer.pal(length(categories), "Greys")
# The legend's data, colours, orientation, justification, size and spacing are defined
res <- map_ng(data = df, legend = FALSE)
legend("top", categories, fill = colors, horiz = TRUE, xjust = .8, cex = .55, x.intersp = .5)
So much more can be done with this; details can be found in the documentation via ?legend.
Installation
The new version of the package can be installed from CRAN with the following code:
install.packages("naijR")
Feedback on the package is welcome – feel free to post a GitHub issue at https://github.com/BroVic/naijR
Happy coding!
The Opportunist 