## [1] 6 6 3 2 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 8
## 4 Stat4 9
## 5 Stat5 9
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 7
## 3 Stat3 12
## 4 Stat4 13
## 5 Stat5 5
## 6 Stat6 9
## [1] 5 5 5 4 2
## Statistic Value
## 1 Stat1 17
## 2 Stat2 11
## 3 Stat3 11
## 4 Stat4 9
## 5 Stat5 8
## 6 Stat6 8
## Statistic Value
## 1 Stat1 17
## 2 Stat2 10
## 3 Stat3 12
## 4 Stat4 10
## 5 Stat5 7
## 6 Stat6 8
## [1] 6 5 4 3 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 10
## 4 Stat4 9
## 5 Stat5 8
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 8
## 3 Stat3 12
## 4 Stat4 11
## 5 Stat5 6
## 6 Stat6 9
## [1] 2 2 2 1 1
## Statistic Value
## 1 Stat1 14
## 2 Stat2 11
## 3 Stat3 11
## 4 Stat4 9
## 5 Stat5 10
## 6 Stat6 9
## Statistic Value
## 1 Stat1 14
## 2 Stat2 10
## 3 Stat3 12
## 4 Stat4 10
## 5 Stat5 9
## 6 Stat6 9
## [1] 5 4 3 2 1
## Statistic Value
## 1 Stat1 17
## 2 Stat2 10
## 3 Stat3 10
## 4 Stat4 9
## 5 Stat5 9
## 6 Stat6 9
## Statistic Value
## 1 Stat1 17
## 2 Stat2 8
## 3 Stat3 12
## 4 Stat4 11
## 5 Stat5 7
## 6 Stat6 9
## [1] 4 4 2 1 1
## Statistic Value
## 1 Stat1 16
## 2 Stat2 11
## 3 Stat3 9
## 4 Stat4 9
## 5 Stat5 10
## 6 Stat6 9
## Statistic Value
## 1 Stat1 16
## 2 Stat2 8
## 3 Stat3 12
## 4 Stat4 12
## 5 Stat5 7
## 6 Stat6 9
## [1] 6 6 3 3 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 8
## 4 Stat4 10
## 5 Stat5 8
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 8
## 3 Stat3 11
## 4 Stat4 13
## 5 Stat5 5
## 6 Stat6 9
## [1] 5 5 3 1 1
## Statistic Value
## 1 Stat1 17
## 2 Stat2 11
## 3 Stat3 9
## 4 Stat4 8
## 5 Stat5 10
## 6 Stat6 9
## Statistic Value
## 1 Stat1 17
## 2 Stat2 7
## 3 Stat3 13
## 4 Stat4 12
## 5 Stat5 6
## 6 Stat6 9
## [1] 4 3 3 3 3
## Statistic Value
## 1 Stat1 16
## 2 Stat2 10
## 3 Stat3 11
## 4 Stat4 10
## 5 Stat5 10
## 6 Stat6 7
## Statistic Value
## 1 Stat1 16
## 2 Stat2 10
## 3 Stat3 11
## 4 Stat4 10
## 5 Stat5 10
## 6 Stat6 7
## [1] 6 6 6 5 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 11
## 4 Stat4 9
## 5 Stat5 6
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 12
## 4 Stat4 10
## 5 Stat5 5
## 6 Stat6 9
## [1] 6 4 2 1 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 9
## 3 Stat3 9
## 4 Stat4 9
## 5 Stat5 10
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 6
## 3 Stat3 12
## 4 Stat4 12
## 5 Stat5 7
## 6 Stat6 9
## [1] 6 6 5 5 3
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 10
## 4 Stat4 10
## 5 Stat5 8
## 6 Stat6 7
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 11
## 4 Stat4 11
## 5 Stat5 7
## 6 Stat6 7
## [1] 6 5 5 2 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 11
## 4 Stat4 7
## 5 Stat5 9
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 7
## 3 Stat3 14
## 4 Stat4 10
## 5 Stat5 6
## 6 Stat6 9
## [1] 6 6 3 2 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 8
## 4 Stat4 9
## 5 Stat5 9
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 7
## 3 Stat3 12
## 4 Stat4 13
## 5 Stat5 5
## 6 Stat6 9
## [1] 6 6 5 3 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 10
## 4 Stat4 8
## 5 Stat5 8
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 8
## 3 Stat3 13
## 4 Stat4 11
## 5 Stat5 5
## 6 Stat6 9
## [1] 6 6 6 5 4
## Statistic Value
## 1 Stat1 18
## 2 Stat2 11
## 3 Stat3 11
## 4 Stat4 9
## 5 Stat5 9
## 6 Stat6 6
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 12
## 4 Stat4 10
## 5 Stat5 8
## 6 Stat6 6
## [1] 4 4 4 2 1
## Statistic Value
## 1 Stat1 16
## 2 Stat2 11
## 3 Stat3 11
## 4 Stat4 8
## 5 Stat5 9
## 6 Stat6 9
## Statistic Value
## 1 Stat1 16
## 2 Stat2 9
## 3 Stat3 13
## 4 Stat4 10
## 5 Stat5 7
## 6 Stat6 9
## [1] 6 5 3 1 1
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 9
## 4 Stat4 8
## 5 Stat5 10
## 6 Stat6 9
## Statistic Value
## 1 Stat1 18
## 2 Stat2 6
## 3 Stat3 13
## 4 Stat4 12
## 5 Stat5 6
## 6 Stat6 9
## [1] 5 5 4 2 1
## Statistic Value
## 1 Stat1 17
## 2 Stat2 11
## 3 Stat3 10
## 4 Stat4 8
## 5 Stat5 9
## 6 Stat6 9
## Statistic Value
## 1 Stat1 17
## 2 Stat2 8
## 3 Stat3 13
## 4 Stat4 11
## 5 Stat5 6
## 6 Stat6 9
## [1] 6 4 4 2 2
## Statistic Value
## 1 Stat1 18
## 2 Stat2 9
## 3 Stat3 11
## 4 Stat4 8
## 5 Stat5 10
## 6 Stat6 8
## Statistic Value
## 1 Stat1 18
## 2 Stat2 7
## 3 Stat3 13
## 4 Stat4 10
## 5 Stat5 8
## 6 Stat6 8
# In For Coin and Blood You Roll 5 Dice and Add them in a Sequence to Selected Values
## Roll the dice
n=5
array2 <- sample(seq(1,6), n, replace = T)
# Sort the Dice from Highest to Lowest
array2 <- sort(array2, decreasing = TRUE)
print(array2)
## [1] 6 5 4 3 3
# Using Dice in Decending Order
# FIrst Assign Each Die from Highest to Lowest
Die1b <- array2[1]
Die2b <- array2[2]
Die3b <- array2[3]
Die4b <- array2[4]
Die5b <- array2[5]
# Now Add Those Respective Dice to the Stats in Order from Highest Die to Lowest Die
Stat1b <- 12 + Die1b
Stat2b <- 11 - Die1b + Die2b
Stat3b <- 11 - Die2 + Die3b
Stat4b <- 10 - Die3b + Die4b
Stat5b <- 10 - Die4b + Die5b
Stat6b <- 10 - Die5b
StatArray3 <- c(Stat1b, Stat2b, Stat3b, Stat4b, Stat5b, Stat6b)
df3 <- data.frame("Statistic" = c("Stat1", "Stat2", "Stat3", "Stat4", "Stat5", "Stat6"), "Value" = StatArray3)
print(df3)
## Statistic Value
## 1 Stat1 18
## 2 Stat2 10
## 3 Stat3 11
## 4 Stat4 9
## 5 Stat5 10
## 6 Stat6 7
# This Gives us a Highly Focused Character with 1 Very High Stat and the Rest of the Stats Average
# We Can Instead Generate a Character with a Very High Primary Stat and More Mixed Array
# We Still Add Highest Value to Our Primary Stat and Lowest Value to the Last Stat, but We then Take Second Lowest Value as Die 2 and the Second Highest Die as Die 4.
Die1c <- array2[1]
Die2c <- array2[4]
Die3c <- array2[3]
Die4c <- array2[2]
Die5c <- array2[5]
Stat1c <- 12 + Die1c
Stat2c <- 11 - Die1c + Die2c
Stat3c <- 11 - Die2c + Die3c
Stat4c <- 10 - Die3c + Die4c
Stat5c <- 10 - Die4c + Die5c
Stat6c <- 10 - Die5c
StatArray4 <- c(Stat1c, Stat2c, Stat3c, Stat4c, Stat5c, Stat6c)
df4 <- data.frame("Statistic" = c("Stat1", "Stat2", "Stat3", "Stat4", "Stat5", "Stat6"), "Value" = StatArray4)
print(df4)
## Statistic Value
## 1 Stat1 18
## 2 Stat2 8
## 3 Stat3 12
## 4 Stat4 11
## 5 Stat5 8
## 6 Stat6 7
## Lastly, We Can Play Around Even More by Putting the Third Lowest Roll (the Middle Roll) in the Primary Stat
Die1d <- array2[3]
Die2d <- array2[4]
Die3d <- array2[1]
Die4d <- array2[2]
Die5d <- array2[5]
Stat1d <- 12 + Die1d
Stat2d <- 11 - Die1d + Die2d
Stat3d <- 11 - Die2d + Die3d
Stat4d <- 10 - Die3d + Die4d
Stat5d <- 10 - Die4d + Die5d
Stat6d <- 10 - Die5d
StatArray5 <- c(Stat1d, Stat2d, Stat3d, Stat4d, Stat5d, Stat6d)
df5 <- data.frame("Statistic" = c("Stat1", "Stat2", "Stat3", "Stat4", "Stat5", "Stat6"), "Value" = StatArray5)
print(df5)
## Statistic Value
## 1 Stat1 16
## 2 Stat2 10
## 3 Stat3 14
## 4 Stat4 9
## 5 Stat5 8
## 6 Stat6 7