如何根据R中的日期值创建新值

Question

我有一个像这样的大数据框：

df <- data.frame(id = c('1', '2', '3', '4', '5', '6'), Date = c("01-Feb-17", "05-Feb-17", "03-May-17","24-May-17","20-Oct-17", "25-Oct-17"), Name=c("John", "Jack", "Jack", "John", "John", "Jack"), Workout=c('150', '130', '140', '160', '150', '130'))

如何创建一个新值（Average_Workout），其中包含＆＃34; Workout＆＃34;的平均值。自年初以来的每个时期。

例如，

Answer 1

我们可以在按名称＆＃39;

分组后使用cummean

library(dplyr)
res <- df %>%
         #if not ordered by 'Date' 
         #arrange(Name, as.Date(Date, "%d-%b-%y")) %>%
         group_by(Name) %>%
         mutate(Avg = cummean(Workout))

as.data.frame(res)
#  id      Date Name Workout      Avg
#1  1 01-Feb-17 John     150 150.0000
#2  2 05-Feb-17 Jack     130 130.0000
#3  3 03-May-17 Jack     140 135.0000
#4  4 24-May-17 John     160 155.0000
#5  5 20-Oct-17 John     150 153.3333
#6  6 25-Oct-17 Jack     130 133.3333

注意：当我们引用numeric元素时，它将是character或factor类，具体取决于stringAsFactors = FALSE还是TRUE

数据

df <- data.frame(id = c('1', '2', '3', '4', '5', '6'), 
  Date = c("01-Feb-17", "05-Feb-17", "03-May-17","24-May-17","20-Oct-17", "25-Oct-17"), 
  Name=c("John", "Jack", "Jack", "John", "John", "Jack"), 
  Workout=c(150, 130, 140, 160, 150, 130), stringsAsFactors = FALSE)