使用聚合函数以特定方式处理NA

Question

我有一个如下所示的数据框：

Project Week Number
Project1   01  46.0
Project2   01  46.4
Project3   01 105.0
Project1   02  70.0
Project2   02  84.0
Project3   02  34.8
Project1   03  83.0
Project3   03  37.9

修改

> dput(my.df)
structure(list(Project = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 
1L, 3L), .Label = c("Project1", "Project2", "Project3"), class = "factor"), 
    Week = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L), Number = c(46, 
    46.4, 105, 70, 84, 34.8, 83, 37.9)), .Names = c("Project", 
"Week", "Number"), class = "data.frame", row.names = c(NA, -8L
))

我想计算每周每个项目的总和。

所以我使用聚合函数：

aggregate(Number ~ Project + Week, data = my.df, sum)

如您所见，第3周Project2没有任何价值。

使用聚合函数只需将其留空。 我想要的是用0填充该行。

我试过了：

aggregate(Number ~ Project + Week, data = my.df, sum, na.action = 0)

和

aggregate(Number ~ Project + Week, data = my.df, sum, na.action = function(x) 0)

但没有工作。 有什么想法吗？

Answer 1

您可以使用xtabs()：

my.df <- read.table(header=TRUE, text=
'Project Week Number
Project1   01  46.0
Project2   01  46.4
Project3   01 105.0
Project1   02  70.0
Project2   02  84.0
Project3   02  34.8
Project1   03  83.0
Project3   03  37.9')
my.df$Week <- paste0("0", my.df$Week)

xtabs(Number ~ Project+Week, data=my.df)
#           Week
# Project       01    02    03
#   Project1  46.0  70.0  83.0
#   Project2  46.4  84.0   0.0
#   Project3 105.0  34.8  37.9
as.data.frame(xtabs(Number ~ Project+Week, data=my.df))
#    Project Week  Freq
# 1 Project1   01  46.0
# 2 Project2   01  46.4
# 3 Project3   01 105.0
# 4 Project1   02  70.0
# 5 Project2   02  84.0
# 6 Project3   02  34.8
# 7 Project1   03  83.0
# 8 Project2   03   0.0
# 9 Project3   03  37.9

Answer 2

我们还可以使用complete包中的tidyr函数填写Project2中Week 3的值。之后，我们可以汇总数据。

library(tidyr)

my.df2 <- my.df %>% 
  complete(Project, Week, fill = list(Number = 0))

my.df2

# # A tibble: 9 x 3
#    Project  Week Number
#      <chr> <chr>  <dbl>
# 1 Project1    01   46.0
# 2 Project1    02   70.0
# 3 Project1    03   83.0
# 4 Project2    01   46.4
# 5 Project2    02   84.0
# 6 Project2    03    0.0
# 7 Project3    01  105.0
# 8 Project3    02   34.8
# 9 Project3    03   37.9

数据

my.df <- read.table(text = "Project Week Number
Project1   '01'  46.0
                 Project2   01  46.4
                 Project3   01 105.0
                 Project1   02  70.0
                 Project2   02  84.0
                 Project3   02  34.8
                 Project1   03  83.0
                 Project3   03  37.9",
                 header = TRUE, stringsAsFactors = FALSE)

my.df$Week <- paste0("0", my.df$Week)

Answer 3

或者您可以使用spread中的tidyr fill = 0

aggregate(Number ~ Project + Week, data = my.df, sum) %>% 
  spread(key = Week,value = Number,fill = 0)

然后使用聚集将其恢复为原始格式

aggregate(Number ~ Project + Week, data = my.df, sum) %>% 
  spread(key = Week,value = Number,fill = 0) %>% 
  gather(key = Week, value = Number,`1`,`2`,`3`)