Add/Merge/Melt 只给出特定的列并给出一个唯一的行

Question

我正在尝试转换在某个日期有多个产品销售的数据集。最后，我只想保留包含每天产品销售额总和的唯一列。

我的 MRE：

df <- data.frame(created = as.Date(c("2020-01-01", "2020-01-01", "2020-01-02", "2020-01-02", "2020-01-03", "2020-01-03"), "%Y-%m-%d", tz = "GMT"),
                soldUnits = c(1, 1, 1, 1, 1, 1),
Weekday = c("Mo","Mo","Tu","Tu","Th","Th"),
Sunshinehours = c(7.8,7.8,6.0,6.0,8.0,8.0))

看起来像这样：

       Date   soldUnits Weekday Sunshinehours
     2020-01-01   1       Mo      7.8
     2020-01-01   1       Mo      7.8
     2020-01-02   1       Tu      6.0
     2020-01-02   1       Tu      6.0
     2020-01-03   1       We      8.0
     2020-01-03   1       We      8.0

变形后应该是这样的：

       Date   soldUnits Weekday Sunshinehours
     2020-01-01   2      Mo      7.8
     2020-01-02   2      Tu      6.0
     2020-01-03   2      We      8.0

我尝试了 aggregate() 和 group_by 但没有成功，因为我的数据被丢弃了。

有没有人知道如何根据我提到的规范转换和清理我的数据集？

Answer 1

使用 base 和 dplyr R

df1 = aggregate(df["Sunshinehours"], by=df["created"], mean)
df2 = aggregate(df["soldUnits"], by=df["created"], sum)
df3 = inner_join(df1, df2)

#converting `Weekday` to factors 
df$Weekday = as.factor(df$Weekday)
df3$Weekday = levels(df$Weekday)
     created Sunshinehours soldUnits Weekday
1 2020-01-01           7.8         2      Mo
2 2020-01-02           6.0         2      Th
3 2020-01-03           8.0         2      Tu

Answer 2

可以使用 collap

将不同的函数应用于不同的列（或一组列）

library(collapse)
collap(df, ~ created + Weekday, 
    custom = list(fmean = "Sunshinehours", fsum = "soldUnits"))
     created soldUnits Weekday Sunshinehours
1 2020-01-01         2      Mo           7.8
2 2020-01-02         2      Tu           6.0
3 2020-01-03         2      Th           8.0

Answer 3

这可行：

library(tidyverse)

df %>%
  group_by(created) %>% 
  count(Weekday, Sunshinehours, wt = soldUnits,name = "soldUnits")
#> # A tibble: 3 × 4
#> # Groups:   created [3]
#>   created    Weekday Sunshinehours soldUnits
#>   <date>     <chr>           <dbl>     <dbl>
#> 1 2020-01-01 Mo                7.8         2
#> 2 2020-01-02 Tu                6           2
#> 3 2020-01-03 Th                8           2

^{由 reprex package (v2.0.1)}

于 2021-12-04 创建

Answer 4

另一种dplyr方法：

df %>% 
  group_by(created, Weekday, Sunshinehours) %>% 
  summarise(soldUnits = sum(soldUnits))

  created    Weekday Sunshinehours soldUnits
  <date>     <chr>           <dbl>     <dbl>
1 2020-01-01 Mo                7.8         2
2 2020-01-02 Tu                6           2
3 2020-01-03 Th                8           2

Add/Merge/Melt 只给出特定的列并给出一个唯一的行

Add/Merge/Melt only specific columns and give out one unique row

r

dplyr

data-analysis