在R中使用expss包创建表时,如何获得嵌套变量中要计算的row_percentages?在下面的示例中,我希望在每个时间段内计算行百分比。因此,我希望行百分比在每个时间段(2015-2016年和2017-2018年)内总计为100%。但是现在,百分比是在整个行中计算的。
library(expss)
data(mtcars)
mtcars$period <- "2015-2016"
mtcars <- rbind(mtcars, mtcars)
mtcars$period[33:64] <- "2017-2018"
mtcars = apply_labels(mtcars,
cyl = "Number of cylinders",
am = "Transmission",
am = c("Automatic" = 0,
"Manual"=1),
period = "Measurement period"
)
mtcars %>%
tab_cells(cyl) %>%
tab_cols(period %nest% am) %>%
tab_stat_rpct(label = "row_perc") %>%
tab_pivot()
由reprex package(v0.3.0)于2019-09-28创建
| | | | Measurement period | | | |
| | | | 2015-2016 | | 2017-2018 | |
| | | | Transmission | | Transmission | |
| | | | Automatic | Manual | Automatic | Manual |
| ------------------- | ------------ | -------- | ------------------ | ------ | ------------ | ------ |
| Number of cylinders | 4 | row_perc | 13.6 | 36.4 | 13.6 | 36.4 |
| | 6 | row_perc | 28.6 | 21.4 | 28.6 | 21.4 |
| | 8 | row_perc | 42.9 | 7.1 | 42.9 | 7.1 |
| | #Total cases | row_perc | 19.0 | 13.0 | 19.0 | 13.0 |
答案 0 :(得分:1)
我相信这就是你所追求的:
library(expss)
data(mtcars)
mtcars$period <- "2015-2016"
mtcars <- rbind(mtcars, mtcars)
mtcars$period[33:64] <- "2017-2018"
mtcars = apply_labels(mtcars,
cyl = "Number of cylinders",
am = "Transmission",
am = c("Automatic" = 0,
"Manual"=1),
period = "Measurement period"
)
mtcars %>%
tab_cells(cyl) %>%
tab_cols(period %nest% am ) %>%
tab_subgroup(period =="2015-2016") %>%
tab_stat_rpct(label = "row_perc") %>%
tab_subgroup(period =="2017-2018") %>%
tab_stat_rpct(label = "row_perc") %>%
tab_pivot(stat_position = "inside_rows")
请注意tab_subgroup()
的使用,它决定了我们要计算百分比的年份,而stat_position = "inside_rows"
的使用则决定了我们要将计算的输出放在最终表中的位置
输出:
| | | | Measurement period | | | |
| | | | 2015-2016 | | 2017-2018 | |
| | | | Transmission | | Transmission | |
| | | | Automatic | Manual | Automatic | Manual |
| ------------------- | ------------ | -------- | ------------------ | ------ | ------------ | ------ |
| Number of cylinders | 4 | row_perc | 27.3 | 72.7 | | |
| | | | | | 27.3 | 72.7 |
| | 6 | row_perc | 57.1 | 42.9 | | |
| | | | | | 57.1 | 42.9 |
| | 8 | row_perc | 85.7 | 14.3 | | |
| | | | | | 85.7 | 14.3 |
| | #Total cases | row_perc | 19.0 | 13.0 | | |
| | | | | | 19.0 | 13.0 |
编辑:
如果我们不希望嵌套的行(即多出两倍的行),则不需要%nest%
。在这种情况下,应对代码的最后部分进行如下修改:
mtcars %>%
tab_cells(cyl) %>%
tab_cols(period,am) %>%
tab_subgroup(period ==c("2015-2016")) %>%
tab_stat_rpct(label = "row_perc") %>%
tab_subgroup(period ==c("2017-2018")) %>%
tab_stat_rpct(label = "row_perc") %>%
tab_pivot(stat_position = "outside_columns")
输出:
| | | Measurement period | Transmission | | |
| | | 2015-2016 | Automatic | Manual | Automatic |
| | | row_perc | row_perc | row_perc | row_perc |
| ------------------- | ------------ | ------------------ | ------------ | -------- | --------- |
| Number of cylinders | 4 | 100 | 27.3 | 72.7 | 27.3 |
| | 6 | 100 | 57.1 | 42.9 | 57.1 |
| | 8 | 100 | 85.7 | 14.3 | 85.7 |
| | #Total cases | 32 | 19.0 | 13.0 | 19.0 |
| Measurement period |
Manual | 2017-2018 |
row_perc | row_perc |
-------- | ------------------ |
72.7 | 100 |
42.9 | 100 |
14.3 | 100 |
13.0 | 32 |