在 R 中使用 dplyr 重塑表格

Question

欢迎在 R 中正确应用 dplyr 的小建议。 我们有以下数据：

   City            Amount    Category
1  Los Angeles     100       Film
2  Los Angeles     200       Film
3  Los Angeles     400       Music 
4  Seattle         300       Coffee
5  Boston          600       Books
...

最终结果应如下所示：

                        Film   Coffee   Books   ...
City  
Los Angeles, CA         Sum    Sum      Sum     Sum 
Seattle, WA             Sum    Sum      Sum     Sum 
Boston, MA              Sum    Sum      Sum     Sum  

我希望数据透视表汇总每个城市中每个类别的“金额”总值，以便城市在左侧列中，所有类别在顶部作为一行。

试过了：

data %>%                                            
  group_by(Location, Category) %>%
  summarise(Amount = sum(Amount))

看起来更像

   City            Amount    Category
1  Los Angeles     300       Film
3  Los Angeles     400       Music 
4  Seattle         300       Coffee
5  Boston          600       Books

计算是正确的，但如上所述，我们需要将 City 和 Category 作为矩阵，其中包含相应单元格内每个 Amount 的总和。

感谢您的帮助！

Answer 1

您正在寻找的是 tidyr::spread 将您的 data.frame 从长格式重塑为宽格式：

library(tidyverse)

# recreate the data
data <- tribble(
  ~City,             ~Amount,   ~Category,
  "Los Angeles",     100,       "Film",
  "Los Angeles",     200,       "Film",
  "Los Angeles",     400,       "Music", 
  "Seattle",         300,       "Coffee",
  "Boston",          600,       "Books"
)

# using your code to get the data in the long-format
data_long <- data %>% 
  group_by(City, Category) %>%
  summarise(Amount = sum(Amount))

data_long
#> # A tibble: 4 x 3
#> # Groups:   City [?]
#>          City Category Amount
#>         <chr>    <chr>  <dbl>
#> 1      Boston    Books    600
#> 2 Los Angeles     Film    300
#> 3 Los Angeles    Music    400
#> 4     Seattle   Coffee    300

# spread to wide using the tidyr-package (in tidyverse)
data_wide <- spread(data_long, key = "Category", value = "Amount", fill = 0)

data_wide
#> # A tibble: 3 x 5
#> # Groups:   City [3]
#>          City Books Coffee  Film Music
#> *       <chr> <dbl>  <dbl> <dbl> <dbl>
#> 1      Boston   600      0     0     0
#> 2 Los Angeles     0      0   300   400
#> 3     Seattle     0    300     0     0

迈向矩阵

mat <- as.matrix(data_wide %>% ungroup %>% select(-City))
rownames(mat) <- data_wide$City

mat
#>             Books Coffee Film Music
#> Boston        600      0    0     0
#> Los Angeles     0      0  300   400
#> Seattle         0    300    0     0

str(mat)
#>  num [1:3, 1:4] 600 0 0 0 0 300 0 300 0 0 ...
#>  - attr(*, "dimnames")=List of 2
#>   ..$ : chr [1:3] "Boston" "Los Angeles" "Seattle"
#>   ..$ : chr [1:4] "Books" "Coffee" "Film" "Music"