关于数据框：R：根据模拟结果填充数据框的一列

R: populating a column of a data frame based on results of simulation

问题继续：
当结果是字符串且顺序不同时，删除重复的结果

我想创建一个数据框，其中包含掷两个骰子的可能结果。这样做的目的是单独运行模拟并用结果数量填充数据框。我编写了以下代码来创建数据框：

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# Create variables in data frame
dice1 <- sort(rep(1:6,6))
dice2 <- rep(1:6,6)
dicesum <- dice1 + dice2

# Assign variables to data frame
df <- data.frame(dice1, dice2, dicesum)

# Remove duplicates
inx <- duplicated(t(apply(df, 1, sort)))
df <- df[!inx, ]
rownames(df) <- 1:nrow(df)

# initiate a column that holds the simulation outcome count
df[“count”] <- numeric(nrow(df))

> str(df)
‘data.frame’: 21 obs. of 4 variables:
$ dice1 : int 1 1 1 1 1 1 2 2 2 2 …
$ dice2 : int 1 2 3 4 5 6 2 3 4 5 …
$ dicesum: int 2 3 4 5 6 7 4 5 6 7 …
$ count : num 0 0 0 0 0 0 0 0 0 0 …

> head(df)
dice1 dice2 dicesum count
1 1 1 2 0
2 1 2 3 0
3 1 3 4 0
4 1 4 5 0
5 1 5 6 0
6 1 6 7 0

# Simulate dice rolls
sim_dice1 <- sample(1:6, 100, replace = T)
sim_dice2 <- sample(1:6, 100, replace = T)

# Data frame with simulations
rolls <- data.frame(sim_dice1, sim_dice2)

> str(rolls)
‘data.frame’: 100 obs. of 2 variables:
$ sim_dice1: int 2 1 5 2 4 2 1 4 6 1 …
$ sim_dice2: int 6 5 4 1 4 5 4 5 6 2 …

> head(rolls)
sim_dice1 sim_dice2
1 2 6
2 1 5
3 5 4
4 2 1
5 4 4
6 2 5

用模拟结果填充 df 中的”count”列的最佳方法是什么？请注意，模拟数据框具有重复的结果 – 我认为 (1,6) 和 (6,1) 是重复的结果。

相关讨论

我将创建一个带有骰子一、骰子二的数据框，使用循环或应用函数运行滚动，并且每次 rbind 结果。然后，当一切都完成后， group_by (dice1, dice2)%>%summarize(count=n(), dicesum=sum(dice1, dice2)) 你就会有一张桌子，里面有你想要的东西。

我们可以使用dplyr包来完成这个任务。

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library(dplyr)

# Create and count the number of each Group
rolls2 <- rolls %>%
rowwise() %>%
mutate(Group = toString(sort(c(sim_dice1, sim_dice2)))) %>%
ungroup() %>%
count(Group)

# Create the Group name
df2 <- df %>%
rowwise() %>%
mutate(Group = toString(sort(c(dice1, dice2))))

# Perform merge between df2 and rolls2
df3 <- df2 %>%
left_join(rolls2, by =”Group”) %>%
select(-Group) %>%
rename(count = n) %>%
replace(is.na(.), 0)

df3
Source: local data frame [21 x 4]
Groups: <by row>

# A tibble: 21 x 4
dice1 dice2 dicesum count
<int> <int> <int> <dbl>
1 1 1 2 0
2 1 2 3 5
3 1 3 4 5
4 1 4 5 8
5 1 5 6 4
6 1 6 7 5
7 2 2 4 2
8 2 3 5 8
9 2 4 6 7
10 2 5 7 7
# … with 11 more rows

数据

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# Create variables in data frame
dice1 <- sort(rep(1:6,6))
dice2 <- rep(1:6,6)
dicesum <- dice1 + dice2

# Assign variables to data frame
df <- data.frame(dice1, dice2, dicesum)

# Remove duplicates
inx <- duplicated(t(apply(df, 1, sort)))
df <- df[!inx, ]
rownames(df) <- 1:nrow(df)

# Set seed for the reproducibility
set.seed(123)

# Simulate dice rolls
sim_dice1 <- sample(1:6, 100, replace = T)
sim_dice2 <- sample(1:6, 100, replace = T)

# Data frame with simulations
rolls <- data.frame(sim_dice1, sim_dice2)

这是你要找的吗：

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> # reduce to 10 simulation for illustration
> set.seed(17699398)
> sim_dice1 <- sample(1:6, 10, replace = T)
> sim_dice2 <- sample(1:6, 10, replace = T)
>
> sim_sum <- sim_dice1 + sim_dice2
>
> # print for illustration
> cbind(sim_dice1, sim_dice2, sim_sum)
sim_dice1 sim_dice2 sim_sum
[1,] 6 5 11
[2,] 3 1 4
[3,] 3 2 5
[4,] 6 5 11
[5,] 3 6 9
[6,] 3 2 5
[7,] 1 5 6
[8,] 1 2 3
[9,] 2 4 6
[10,] 2 2 4
>
> # make table
> sim_outcome <- table(sim_sum)
> sim_outcome
sim_sum
3 4 5 6 9 11
1 2 2 2 1 2
>
>
> # use that df and returned object from table function is sorted
> df$count[match(as.integer(names(sim_outcome)), df$dicesum)] <- sim_outcome
>
> df
dice1 dice2 dicesum count
1 1 1 2 0
2 1 2 3 1
3 1 3 4 2
4 1 4 5 2
5 1 5 6 2
6 1 6 7 0
7 2 2 4 0
8 2 3 5 0
9 2 4 6 0
10 2 5 7 0
11 2 6 8 0
12 3 3 6 0
13 3 4 7 0
14 3 5 8 0
15 3 6 9 1
16 4 4 8 0
17 4 5 9 0
18 4 6 10 0
19 5 5 10 0
20 5 6 11 2
21 6 6 12 0

R: populating a column of a data frame based on results of simulation

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