namecount

The namecount package contains 5 functions:getNamesCount, getNamesStart, getNamesUnique, countStart, and countNamesUnique. These functions can be used to count the number of names in a specified column or retrieve names from a specified column.The goal of the getNamesCount package is to provide a quick and easy way to filter your to better understand your data set without having to write out a long function yourself.

Installation

You can install the development version of namecount from GitHub with:

# install.packages("devtools")
devtools::install_github("stat545ubc-2023/namecount")

getNamesCount - Example 1

This is a basic example of the getNamesCount function from the namecount package using a basic data set:

# calling the 'namecount' package
library(namecount)
# basic sample data frame containing numeric and categorical columns 
dfSample <- data.frame(
fruit = c("apple", "banana", "cherry", "coconut", "dragonfruit"),
numFruit = c(17, 90, 35, 49, 102))
# using the 'getNamesCount' function 
answer1.0 <- getNamesCount(dfSample, fruit, numFruit, 50)

print(answer1.0)
#> [1] 3

getNamesCount - Example 2

Looking at the summary statistics from the penguins data set from the palmerpenguins package you can see that the mean bill length collected in the data is 43.92mm.

sumP <- summary(palmerpenguins::penguins)

print(sumP)
#>       species          island    bill_length_mm  bill_depth_mm  
#>  Adelie   :152   Biscoe   :168   Min.   :32.10   Min.   :13.10  
#>  Chinstrap: 68   Dream    :124   1st Qu.:39.23   1st Qu.:15.60  
#>  Gentoo   :124   Torgersen: 52   Median :44.45   Median :17.30  
#>                                  Mean   :43.92   Mean   :17.15  
#>                                  3rd Qu.:48.50   3rd Qu.:18.70  
#>                                  Max.   :59.60   Max.   :21.50  
#>                                  NA's   :2       NA's   :2      
#>  flipper_length_mm  body_mass_g       sex           year     
#>  Min.   :172.0     Min.   :2700   female:165   Min.   :2007  
#>  1st Qu.:190.0     1st Qu.:3550   male  :168   1st Qu.:2007  
#>  Median :197.0     Median :4050   NA's  : 11   Median :2008  
#>  Mean   :200.9     Mean   :4202                Mean   :2008  
#>  3rd Qu.:213.0     3rd Qu.:4750                3rd Qu.:2009  
#>  Max.   :231.0     Max.   :6300                Max.   :2009  
#>  NA's   :2         NA's   :2

Now I would like to know how many observations there are in the data set for species of penguins with a bill length below the mean collected. This is where I would use the namecount function:

library(namecount)

answer2.0 <- getNamesCount(palmerpenguins::penguins, species, bill_length_mm, 43.92)

print(answer2.0)
#> [1] 167

The getNamesCount function produced a number, this number is the total species observations that have a corresponding bill length measurement below the numericalValue that was set at the mean (43.92mm)

Conclusion

If you would like to see more examples of usage for the namecount package please refer to the package vignette or function help pages.

Website

Link to pkgdown website

References

The source of the penguins data set from the palmerpenguins R package used here:

Horst AM, Hill AP, Gorman KB (2020). palmerpenguins: Palmer Archipelago (Antarctica) penguin data. doi:10.5281/zenodo.3960218, R package version 0.1.0, https://allisonhorst.github.io/palmerpenguins/.