pivot_wider，计数出现次数 [英] pivot_wider, count number of occurrences

问题描述

简单的问题.我想在数据集上使用 pivot_wider 来计算每个类别的出现次数:

Simple question. I'd like to use pivot_wider on a dataset to count the number of occurrences of each category:

这是一个包含数据 mtcars 的示例(我将它们按 cyl 分组，然后计算不同碳水化合物的出现次数)

Here is an example with the data mtcars (where I group them by cyl, and then count up the occurrences of the different carbs)

mtcars %>%
  dplyr::group_by(cyl,carb) %>%
  dplyr::summarize(sum=n()) %>%
  pivot_wider(id_cols="cyl",names_from="carb",values_from="sum")

# A tibble: 3 x 7
# Groups:   cyl [3]
    cyl   `1`   `2`   `4`   `6`   `3`   `8`
  <dbl> <int> <int> <int> <int> <int> <int>
1     4     5     6    NA    NA    NA    NA
2     6     2    NA     4     1    NA    NA
3     8    NA     4     6    NA     3     1

有没有办法让我直接使用pivot_wider"来做到这一点?我可以用'dcast'来做到这一点

Is there a way for me to do this directly with 'pivot_wider'? I can do this with 'dcast'

mtcars %>%
  dcast(cyl~carb,fun.aggregate=length)

Using carb as value column: use value.var to override.
  cyl 1 2 3 4 6 8
1   4 5 6 0 0 0 0
2   6 2 0 0 4 1 0
3   8 0 4 3 6 0 1

...但我喜欢将pivot_wider"用于其他很多事情(它的语法对我来说很有意义).

...but I like using 'pivot_wider' for a lot of other things (its syntax makes sense to me).

谢谢！

推荐答案

您可以将 values_fn 参数用于 pivot_wider，其作用与 fun 相同.aggregate 在 dcast 中.

You can use the values_fn argument to pivot_wider, which plays the same role as fun.aggregate in dcast.

mtcars %>%
    pivot_wider(id_cols = "cyl",
                names_from = "carb",
                values_from = "am",
                values_fn = list(am = length))

请注意，您必须选择一列(我随意选择了am)，然后将values_fn 作为命名列表(假设您想取其长度)柱子).这是一个命名列表，因为在其他用例中，您可能会聚合多个列.

Note that you have to pick a column (arbitrarily, I chose am), and give values_fn as a named list (saying you want to take the length of that column). It's a named list because in other use cases you could be aggregating multiple columns.

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