The plyr package uses **ply() functions, where the first star in the input and the second star is the output. For example, llplyr takes a list in and spits a list out.

Want to learn more? I recommend working through: R for Data Science, R Cookbook, and R Graphics Cookbook.

```# load the plyr package
library(plyr)
```
```#generate some fake list data
war.name <- c("WWII", "WWII", "WWI", "WWI", "Franco-Prussian", "Franco-Prussian", "Franco-Prussian", "Boer War", "Boer War", "Boer War")
deaths <- c(938, 9480, 2049, 1039, 3928, 9202, 10933, 40293, 10394, 20394)
allies <- c(9, 5, 4, 6, 3, 2, 4, 1, 2, 3)
casualties <- list(war.name, deaths, allies)
casualties.df <- data.frame(war.name, deaths, allies)
```
```# split up the list by casualties, find all the unique elements, output them as a list
llply(casualties, unique)
```
```[[1]]
[1] "WWII"            "WWI"             "Franco-Prussian" "Boer War"

[[2]]
[1]   938  9480  2049  1039  3928  9202 10933 40293 10394 20394

[[3]]
[1] 9 5 4 6 3 2 1
```

r*ply replaces replicate, with the * denoting the output

```# run runif(1) five times, outputting a data frame
rdply(5, runif(1))
```
```  .n         V1
1  1 0.09292281
2  2 0.06861817
3  3 0.04870200
4  4 0.57864348
5  5 0.21716079
```

ddply replaces tapply, it inputs a data frame and outputs a data frame

```# take the data frame casualties.df, split it up by war.name (for some reasons it uses the .() function, the find the mean)
ddply(
casualties.df,
.(war.name),
colwise(mean)
)
```
```         war.name   deaths allies
1        Boer War 23693.67      2
2 Franco-Prussian  8021.00      3
3             WWI  1544.00      5
4            WWII  5209.00      7
```