Question

我在R工作室的R工作。我需要计算数据框每列的平均值。

 cluster1  // 5 by 4 data frame
 mean(cluster1) //

我得到了：

  Warning message:
  In mean.default(cluster1) :
  argument is not numeric or logical: returning NA

但我可以使用

  mean(cluster1[[1]])

获取第一列的平均值。

如何获取所有列的方法？

任何帮助将不胜感激。

Answer 1

您可以使用colMeans：

### Sample data
set.seed(1)
m <- data.frame(matrix(sample(100, 20, replace = TRUE), ncol = 4))

### Your error
mean(m)
# [1] NA
# Warning message:
# In mean.default(m) : argument is not numeric or logical: returning NA

### The result using `colMeans`
colMeans(m)
#   X1   X2   X3   X4 
# 47.0 64.4 44.8 67.8

Answer 2

您可以使用'apply'来运行函数或矩阵或数值数据框的行或列：

cluster1 <- data.frame(a=1:5, b=11:15, c=21:25, d=31:35)

apply(cluster1,2,mean)  # applies function 'mean' to 2nd dimension (columns)

apply(cluster1,1,mean)  # applies function to 1st dimension (rows)

sapply(cluster1, mean)  # also takes mean of columns, treating data frame like list of vectors

Answer 3

如果你有NA的话：

sapply(data, mean, na.rm = T)      # Returns a vector (with names)   
lapply(data, mean, na.rm = T)      # Returns a list

请记住，“卑鄙”需要数字数据。如果您有混合类数据，请使用：

numdata<-data[sapply(data, is.numeric)]  
sapply(numdata, mean, na.rm = T)  # Returns a vector
lapply(numdata, mean, na.rm = T)  # Returns a list

Answer 4

另一种方法是使用 purrr 包

# example data like what is said above

@A Handcart和Mohair

set.seed(1)
m <- data.frame(matrix(sample(100, 20, replace = TRUE), ncol = 4))


library(purrr)
means <- map_dbl(m, mean)

> means
#  X1   X2   X3   X4 
#47.0 64.4 44.8 67.8

Answer 5

尝试一下！还可以计算NA的数据！

df <- data.frame(a1=1:10, a2=11:20)

df %>% summarise_each(funs( mean( .,na.rm = TRUE)))


# a1   a2
# 5.5 15.5

Answer 6

class(mtcars)
my.mean <- unlist(lapply(mtcars, mean)); my.mean



   mpg        cyl       disp         hp       drat         wt       qsec         vs 
 20.090625   6.187500 230.721875 146.687500   3.596563   3.217250  17.848750   0.437500 
        am       gear       carb 
  0.406250   3.687500   2.812500

Answer 7

对于多样性：另一种方法是将矢量函数转换为使用数据的函数使用plyr::colwise()

的框架

set.seed(1)
m <- data.frame(matrix(sample(100, 20, replace = TRUE), ncol = 4))

plyr::colwise(mean)(m)


#   X1   X2   X3   X4
# 1 47 64.4 44.8 67.8

Answer 8

你可以试试这个：

mean(as.matrix(cluster1))

计算R中矩阵的每列的平均值

8 个答案: