通过多种因素对表格进行分组并将其从长格式扩展到宽格式-R中的data.table方式 [英] grouping table by multiple factors and spreading it from long format to wide - the data.table way in R

问题描述

作为示例，我将使用R中可用的 mtcars 数据：

As an example i will be using the mtcars data available in R:

data(mtcars)
setDT(mtcars)

让我想将数据按三个变量进行分组，分别是： carb ， cyl 和齿轮。我已经做到了如下。但是，我确信有更好的方法，因为这是重复性的。

Lets day I want to group the data by three variables, namely: carb, cyl, and gear. I have done this as follow. However, i am sure there is a better way, as this is quite repetitive.

newDTcars <- mtcars [, mtcars[, mtcars[, .N , by = carb], by = cyl], by= gear]

第二，我希望数据具有较宽的格式，每个 gear 级别都有一个单独的列。为了便于说明，我使用 tidyr 进行了此操作，但是我想使用 data.table方法进行此操作。

Secondly, I would like to have the data in a wide format, where there is a separate column for every gear level. For illustration purpose I have done this using tidyr, however i would like to have this done the "data.table" way.

newDTcars %>% tidyr::spread(gear, N)

这个问题的重点是继续解决data.table世界，因为我也想进一步了解 data。表格。

The emphasis of this question is to keep to solution to the data.table world, as i would like too learn more about data.table.

推荐答案

在 data.table 中，我们可以按多列分组要重塑，我们可以使用 dcast 。

In data.table, we can group by multiple columns and to reshape we can use dcast.

library(data.table)
dcast(mtcars[, .N, .(carb, cyl, gear)], carb+cyl~gear, value.var = "N")

#   carb cyl  3  4  5
#1:    1   4  1  4 NA
#2:    1   6  2 NA NA
#3:    2   4 NA  4  2
#4:    2   8  4 NA NA
#5:    3   8  3 NA NA
#6:    4   6 NA  4 NA
#7:    4   8  5 NA  1
#8:    6   6 NA NA  1
#9:    8   8 NA NA  1

您可以在 dcast 中使用 fill 参数将 NA 替换为0或任何其他数字。

You may use fill argument in dcast to replace NAs with 0 or any other number.

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