License: MIT
This package wraps the pattern of un-tidying data into a wide matrix, performing some processing, then turning it back into a tidy form. This is useful for several mathematical operations such as co-occurence counts, correlations, or clustering that are best done on a wide matrix.
Install from Github with devtools:
library(devtools)
install_github("dgrtwo/widyr")Consider the gapminder dataset in the gapminder package.
library(dplyr)
library(gapminder)
gapminder
#> Source: local data frame [1,704 x 6]
#>
#> country continent year lifeExp pop gdpPercap
#> (fctr) (fctr) (int) (dbl) (int) (dbl)
#> 1 Afghanistan Asia 1952 28.801 8425333 779.4453
#> 2 Afghanistan Asia 1957 30.332 9240934 820.8530
#> 3 Afghanistan Asia 1962 31.997 10267083 853.1007
#> 4 Afghanistan Asia 1967 34.020 11537966 836.1971
#> 5 Afghanistan Asia 1972 36.088 13079460 739.9811
#> 6 Afghanistan Asia 1977 38.438 14880372 786.1134
#> 7 Afghanistan Asia 1982 39.854 12881816 978.0114
#> 8 Afghanistan Asia 1987 40.822 13867957 852.3959
#> 9 Afghanistan Asia 1992 41.674 16317921 649.3414
#> 10 Afghanistan Asia 1997 41.763 22227415 635.3414
#> .. ... ... ... ... ... ...This tidy format (one-row-per-country-per-year) is very useful for grouping, summarizing, and filtering operations. But if we want to compare countries (for example, to find countries that are similar to each other), we would have to reshape this dataset.
The widyr package offers pairwise_ functions that operate on pairs of items within groups. An example is pairwise_dist:
library(widyr)
gapminder %>%
pairwise_dist(country, year, lifeExp)
#> Source: local data frame [20,022 x 3]
#>
#> item1 item2 distance
#> (chr) (chr) (dbl)
#> 1 Albania Afghanistan 107.41825
#> 2 Algeria Afghanistan 76.75286
#> 3 Angola Afghanistan 4.64934
#> 4 Argentina Afghanistan 109.50686
#> 5 Australia Afghanistan 128.95745
#> 6 Austria Afghanistan 123.51771
#> 7 Bahrain Afghanistan 98.13426
#> 8 Bangladesh Afghanistan 45.33990
#> 9 Belgium Afghanistan 125.41156
#> 10 Benin Afghanistan 39.32262
#> .. ... ... ...In a single step, this finds the Euclidean distance between the lifeExp value in each pair of countries, matching by year. We could find the closest pairs of countries overall:
gapminder %>%
pairwise_dist(country, year, lifeExp) %>%
arrange(distance)
#> Source: local data frame [20,022 x 3]
#>
#> item1 item2 distance
#> (chr) (chr) (dbl)
#> 1 Germany Belgium 1.075702
#> 2 Belgium Germany 1.075702
#> 3 United Kingdom New Zealand 1.509025
#> 4 New Zealand United Kingdom 1.509025
#> 5 Norway Netherlands 1.557933
#> 6 Netherlands Norway 1.557933
#> 7 Italy Israel 1.662690
#> 8 Israel Italy 1.662690
#> 9 Finland Austria 1.936558
#> 10 Austria Finland 1.936558
#> .. ... ... ...Notice that this includes duplicates (Germany/Belgium . To avoid those (the upper triangle of the distance matrix), use upper = FALSE:
gapminder %>%
pairwise_dist(country, year, lifeExp, upper = FALSE) %>%
arrange(distance)
#> Source: local data frame [10,011 x 3]
#>
#> item1 item2 distance
#> (chr) (chr) (dbl)
#> 1 Belgium Germany 1.075702
#> 2 New Zealand United Kingdom 1.509025
#> 3 Netherlands Norway 1.557933
#> 4 Israel Italy 1.662690
#> 5 Austria Finland 1.936558
#> 6 Belgium United Kingdom 1.949243
#> 7 Iceland Sweden 2.005176
#> 8 Comoros Mauritania 2.008199
#> 9 Belgium United States 2.092081
#> 10 Germany Ireland 2.097239
#> .. ... ... ...In some analyses, we may be interested in correlation rather than distance of pairs. For this we would use pairwise_cor:
gapminder %>%
pairwise_cor(country, year, lifeExp, upper = FALSE) %>%
arrange(desc(correlation))
#> Source: local data frame [10,011 x 3]
#>
#> item1 item2 correlation
#> (chr) (chr) (dbl)
#> 1 Indonesia Mauritania 0.9996291
#> 2 Morocco Senegal 0.9995515
#> 3 Saudi Arabia West Bank and Gaza 0.9995156
#> 4 Brazil France 0.9994246
#> 5 Bahrain Reunion 0.9993649
#> 6 Malaysia Sao Tome and Principe 0.9993233
#> 7 Peru Syria 0.9993063
#> 8 Bolivia Gambia 0.9992930
#> 9 Indonesia Morocco 0.9992799
#> 10 Libya Senegal 0.9992710
#> .. ... ... ...Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
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