dplyrx is a collection of functions that extend those in the dplyr package.
Installation
You can install dplyrx from github with:
# install.packages("devtools")
devtools::install_github("epix-project/dplyrx")To load the package:
library(dplyrx)Example
Below is a basic example which shows you how to solve a common problem. Imagine that you have a data frame that looks like this:
set.seed(30101976)
data <- expand.grid(letters[1:3], 1:3, 4:6)
data <- cbind(data, data.frame(replicate(3, sample(1:100, nrow(data), TRUE))))where Var1 could be thought of a spatial location name, Var2 and Var3 can be thought of year and month and X1, X2 and X3 can be tought of measured values for given points in space and time. If you want to aggregate the values “a” and “b” of the categorical the variable Var1, summing the values of variables X4, X5 and X6, it can be done like this:
data %>%
mutate(Var1 = recode(Var1, a = "b")) %>%
aggregate_by(Var1, Var2, Var3)
#> # A tibble: 18 x 6
#> # Groups: Var1, Var2 [?]
#> Var1 Var2 Var3 X1 X2 X3
#> <fct> <int> <int> <int> <int> <int>
#> 1 b 1 4 77 136 142
#> 2 b 1 5 119 116 106
#> 3 b 1 6 14 111 107
#> 4 b 2 4 77 122 117
#> 5 b 2 5 78 33 98
#> 6 b 2 6 113 144 171
#> 7 b 3 4 54 81 82
#> 8 b 3 5 139 138 123
#> 9 b 3 6 49 47 58
#> 10 c 1 4 49 12 62
#> 11 c 1 5 5 27 17
#> 12 c 1 6 41 10 43
#> 13 c 2 4 42 9 6
#> 14 c 2 5 27 35 52
#> 15 c 2 6 35 38 3
#> 16 c 3 4 16 2 96
#> 17 c 3 5 21 5 10
#> 18 c 3 6 28 27 7
