自动扩展一个R因子到一个1/0指标变量的集合，每个因子水平

I have an R data frame containing a factor that I want to "expand" so that for each factor level, there is an associated column in a new data frame, which contains a 1/0 indicator. E.g., suppose I have:

我有一个R数据框架，其中包含一个我想要“展开”的因子，以便对于每个因子级别，在一个新的数据框架中有一个相关的列，它包含一个1/0指示器。例如,假设我有:

df.original <-data.frame(eggs = c("foo", "foo", "bar", "bar"), ham = c(1,2,3,4))

I want:

我想要:

df.desired  <- data.frame(foo = c(1,1,0,0), bar=c(0,0,1,1), ham=c(1,2,3,4))

Because for certain analyses for which you need to have a completely numeric data frame (e.g., principal component analysis), I thought this feature might be built in. Writing a function to do this shouldn't be too hard, but I can foresee some challenges relating to column names and if something exists already, I'd rather use that.

因为对于某些分析，您需要拥有一个完整的数字数据框架(例如，主成分分析)，我认为这个特性可能是内置的。编写这样的函数应该不会太难，但我可以预见到与列名相关的一些挑战，如果已经存在某些东西，我宁愿使用它。

8 个解决方案

#1

109

Use the model.matrix function:

使用模型。矩阵函数:

model.matrix( ~ Species - 1, data=iris )

#2

If your data frame is only made of factors (or you are working on a subset of variables which are all factors), you can also use the acm.disjonctif function from the ade4 package :

如果您的数据框架仅由因子组成(或者您正在处理所有因子的变量子集)，您也可以使用acm。disjonctif函数来自ade4包:

R> library(ade4)
R> df <-data.frame(eggs = c("foo", "foo", "bar", "bar"), ham = c("red","blue","green","red"))
R> acm.disjonctif(df)
  eggs.bar eggs.foo ham.blue ham.green ham.red
1        0        1        0         0       1
2        0        1        1         0       0
3        1        0        0         1       0
4        1        0        0         0       1

Not exactly the case you are describing, but it can be useful too...

不完全是你所描述的情况，但它也可能是有用的……

#3

A quick way using the reshape2 package:

使用reshape2包的快速方法:

require(reshape2)

> dcast(df.original, ham ~ eggs, length)

Using ham as value column: use value_var to override.
  ham bar foo
1   1   0   1
2   2   0   1
3   3   1   0
4   4   1   0

Note that this produces precisely the column names you want.

注意，这会生成您想要的列名。

#4

probably dummy variable is similar to what you want. Then, model.matrix is useful:

可能哑变量与你想要的相似。然后,模型。矩阵是有用的:

> with(df.original, data.frame(model.matrix(~eggs+0), ham))
  eggsbar eggsfoo ham
1       0       1   1
2       0       1   2
3       1       0   3
4       1       0   4

#5

A late entry class.ind from the nnet package

晚条目类。从nnet包中获取。

library(nnet)
 with(df.original, data.frame(class.ind(eggs), ham))
  bar foo ham
1   0   1   1
2   0   1   2
3   1   0   3
4   1   0   4

#6

Just came across this old thread and thought I'd add a function that utilizes ade4 to take a dataframe consisting of factors and/or numeric data and returns a dataframe with factors as dummy codes.

刚刚遇到了这个旧线程，并认为我将添加一个函数，该函数利用ade4来获取由factors和/或数值数据组成的dataframe，并将一个dataframe作为虚拟代码返回。

dummy <- function(df) {  

    NUM <- function(dataframe)dataframe[,sapply(dataframe,is.numeric)]
    FAC <- function(dataframe)dataframe[,sapply(dataframe,is.factor)]

    require(ade4)
    if (is.null(ncol(NUM(df)))) {
        DF <- data.frame(NUM(df), acm.disjonctif(FAC(df)))
        names(DF)[1] <- colnames(df)[which(sapply(df, is.numeric))]
    } else {
        DF <- data.frame(NUM(df), acm.disjonctif(FAC(df)))
    }
    return(DF)
}

Let's try it.

让我们试一试。

df <-data.frame(eggs = c("foo", "foo", "bar", "bar"), 
            ham = c("red","blue","green","red"), x=rnorm(4))     
dummy(df)

df2 <-data.frame(eggs = c("foo", "foo", "bar", "bar"), 
            ham = c("red","blue","green","red"))  
dummy(df2)

#7

Here is a more clear way to do it. I use model.matrix to create the dummy boolean variables and then merge it back into the original dataframe.

这里有一个更清晰的方法。我使用模型。矩阵创建假的布尔变量，然后将其合并回原始的dataframe。

df.original <-data.frame(eggs = c("foo", "foo", "bar", "bar"), ham = c(1,2,3,4))
df.original
#   eggs ham
# 1  foo   1
# 2  foo   2
# 3  bar   3
# 4  bar   4

# Create the dummy boolean variables using the model.matrix() function.
> mm <- model.matrix(~eggs-1, df.original)
> mm
#   eggsbar eggsfoo
# 1       0       1
# 2       0       1
# 3       1       0
# 4       1       0
# attr(,"assign")
# [1] 1 1
# attr(,"contrasts")
# attr(,"contrasts")$eggs
# [1] "contr.treatment"

# Remove the "eggs" prefix from the column names as the OP desired.
colnames(mm) <- gsub("eggs","",colnames(mm))
mm
#   bar foo
# 1   0   1
# 2   0   1
# 3   1   0
# 4   1   0
# attr(,"assign")
# [1] 1 1
# attr(,"contrasts")
# attr(,"contrasts")$eggs
# [1] "contr.treatment"

# Combine the matrix back with the original dataframe.
result <- cbind(df.original, mm)
result
#   eggs ham bar foo
# 1  foo   1   0   1
# 2  foo   2   0   1
# 3  bar   3   1   0
# 4  bar   4   1   0

# At this point, you can select out the columns that you want.

#8

I needed a function to 'explode' factors that is a bit more flexible, and made one based on the acm.disjonctif function from the ade4 package. This allows you to choose the exploded values, which are 0 and 1 in acm.disjonctif. It only explodes factors that have 'few' levels. Numeric columns are preserved.

我需要一个函数来“引爆”更灵活的因素，并基于acm制作一个。disjonctif函数来自ade4包。这允许您选择在ac .disjonctif中为0和1的爆炸值。它只会爆炸那些“很少”水平的因素。数字列。

# Function to explode factors that are considered to be categorical,
# i.e., they do not have too many levels.
# - data: The data.frame in which categorical variables will be exploded.
# - values: The exploded values for the value being unequal and equal to a level.
# - max_factor_level_fraction: Maximum number of levels as a fraction of column length. Set to 1 to explode all factors.
# Inspired by the acm.disjonctif function in the ade4 package.
explode_factors <- function(data, values = c(-0.8, 0.8), max_factor_level_fraction = 0.2) {
  exploders <- colnames(data)[sapply(data, function(col){
      is.factor(col) && nlevels(col) <= max_factor_level_fraction * length(col)
    })]
  if (length(exploders) > 0) {
    exploded <- lapply(exploders, function(exp){
        col <- data[, exp]
        n <- length(col)
        dummies <- matrix(values[1], n, length(levels(col)))
        dummies[(1:n) + n * (unclass(col) - 1)] <- values[2]
        colnames(dummies) <- paste(exp, levels(col), sep = '_')
        dummies
      })
    # Only keep numeric data.
    data <- data[sapply(data, is.numeric)]
    # Add exploded values.
    data <- cbind(data, exploded)
  }
  return(data)
}

#1

109