如何计算描述性统计

Question

我有类的数据框，包含名称，性别（女性，男性）和身高的变量。我需要根据性别计算高度变量的描述性统计。我想在输出中的以下内容，任何帮助将不胜感激。

Gender，Freq，Mean，Median，Mode，Std，Dev，min，max

Answer 1

尝试使用此

# assuming df is your data.frame and gender, height are column names 
tapply(df$height, df$gender, function(grp) c(Freq = length(grp), mean = mean(grp),mode = mode(grp),SD = sd(grp),min = min(grp),max = max(grp))) 

Answer 2

功能summarise()从包dplyr将是一个很好的解决方案：

library('dplyr') 
df %>% 
    na.omit %>% 
    group_by(gender) %>% 
    summarise(Freq = n(), #unshure, maybe n()/NROW(df) 
      Mean = mean(height), 
      Median = median(height), 
      Mode = moda(height), 
      Std.Dev = sd(height), 
      min = min(height), 
      max = max(height)) 

凡moda(x)是功能estimatin模式用于从连续可变样品：

moda <- function(x, na.omit = TRUE){ 
    if (na.omit) x <- na.omit(x) 
    d <- density(x) 
    return(d$x[which.max(d$y)]) 
}