Question

我问了一个关于data.table的上一个问题（r - data.table - Why is the data.table result 1 numeric value when it should be rounded to 3 decimal places?）并显示了数字结果。评论提示我只使用by = cyl，但不会给我dplyr结果。因此，我在这里提出一个新问题。

如何使用dplyr获得相同的结果（请参阅下面的data.table代码）？

# using dplyr
mtcars1 %>%
group_by(cyl) %>%
select(disp) %>%
mutate(displace = round(disp / sum(disp), digits = 3))

# Adding missing grouping variables: `cyl`
# Source: local data frame [32 x 3]
# Groups: cyl [3]
# 
#      cyl  disp displace
#    <dbl> <dbl>    <dbl>
# 1      4 108.0    0.093
# 2      4 146.7    0.127
# 3      4 140.8    0.122
# 4      4  78.7    0.068
# 5      4  75.7    0.065
# 6      4  71.1    0.061
# 7      4 120.1    0.104
# 8      4  79.0    0.068
# 9      4 120.3    0.104
# 10     4  95.1    0.082
# # ... with 22 more rows

我试过这个（参见上面提到的上一篇文章）：

# Group cars by number of cylinders and the computed share of displacement
# using data.table
setkey(mtcars2, "cyl")
mtcars2[ , .(displace = round(disp / sum(disp), digits = 3)), by = list(cyl, disp)]

#    cyl  disp displace
#  1:   4 108.0        1
#  2:   4 146.7        1
#  3:   4 140.8        1
#  4:   4  78.7        1
#  5:   4  75.7        1
#  6:   4  71.1        1
#  7:   4 120.1        1
#  8:   4  79.0        1
#  9:   4 120.3        1
# 10:   4  95.1        1
#     cyl  disp displace

这在这里不起作用（尽管它有效：How to group data.table by multiple columns?）

mtcars2[ , displace = round(disp / sum(disp), digits = 3), by = list(cyl, disp)]

# Error in `[.data.table`(mtcars2, , displace = round(disp/sum(disp), digits = 3),  : 
#  unused argument (displace = round(disp/sum(disp), digits = 3))

这并不能提供我想要的所有列（如r - data.table - Why is the data.table result 1 numeric value when it should be rounded to 3 decimal places?中所述）：

mtcars2[ , .(displace = round(disp / sum(disp), digits = 3)), by = cyl]

谢谢。

Answer 1

在data.table中使用:=语法时，即不使用j时，您可以在结果中添加列mtcars2[,.(displace = round(disp / sum(disp), digits = 3), disp), by = cyl] # cyl displace disp # 1: 6 0.125 160.0 # 2: 6 0.125 160.0 # 3: 6 0.201 258.0 # 4: 6 0.175 225.0 # 5: 6 0.131 167.6 # 6: 6 0.131 167.6 # 7: 6 0.113 145.0 # ...列中的列}：

Casing = {}
Casing.__index = Casing
sentArray = {}
function Casing.create(x, y, z)
    if x ~= nil and y ~= nil and z ~= nil then
        local _casing = {}
        setmetatable(_casing,Casing)
        --etc.
        return _casing
    end
end

r - data.table - 使用舍入对多个列分组data.table结果

1 个答案: