我有一个数据框,其中包括离岸(DOS)某些距离的特定日期的不同船舶分类计数,例如: 0-12nm和0-100nm - 我想从0-100nm减去0-12nm DOS内的船只,这样我可以计算多少例如“乘客”船每天只有12-100纳米。一旦完成,我想在整个时间段内每个DOS内计算了多少乘客,货物等船只...我可以找出一个非常费力的方法来做到这一点,但我非常肯定有变异和总结dplyr中的函数有一种更有效的方法来运行它...
这是一个虚拟数据框:
df<- structure(list(date = structure(c(17622, 17623, 17624, 17625,
17626, 17627, 17622, 17623, 17624, 17625, 17626, 17627), class = "Date"),
`Passenger(6X)` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
`Cargo(7X)` = c(2, 0, 2, 2, 2, 3, 5, 4, 7, 6, 7, 4), `Tanker(8X)` = c(0,
0, 0, 0, 0, 0, 0, 3, 1, 0, 1, 0), Otherb = c(`5` = 0, `6` = 0,
`7` = 0, `8` = 0, `9` = 0, `10` = 0, `144` = 0, `154` = 0,
`164` = 0, `174` = 0, `184` = 0, `194` = 0), DOS = c("0-12nm",
"0-12nm", "0-12nm", "0-12nm", "0-12nm", "0-12nm", "0-100nm",
"0-100nm", "0-100nm", "0-100nm", "0-100nm", "0-100nm")), class = "data.frame", row.names = c(1L,
2L, 3L, 4L, 5L, 6L, 1454L, 1455L, 1456L, 1457L, 1458L, 1459L))
在2018年4月1日的这个例子中,12-100nm的货船应该是3 - 输出可以是新柱等形式......在我的实际数据集中,我实际上有4种不同的离岸距离和超过一年的距离日期....所以我认为dplyr是最好的方式 - 任何帮助将不胜感激。
选项1:
df %>%
group_by(date) %>%
summarise_at(
vars(`Cargo(7X)`, `Tanker(8x)`),
funs(.[DOS == '0-100nm'] - .[DOS == '0-12nm'])
)
# date `Cargo(7X)` `Tanker(8x)`
# 1 2018-04-01 3 0
# 2 2018-04-02 4 3
# 3 2018-04-03 5 1
# 4 2018-04-04 4 0
# 5 2018-04-05 5 1
# 6 2018-04-06 1 0
选项2:
df %>%
group_by(date, DOS) %>%
summarise_at(vars(`Cargo(7X)`, `Tanker(8x)`), funs(sum)) %>%
gather(-(date:DOS), key = Ship, value = Value) %>%
spread(key = DOS, value = Value) %>%
mutate('12-100nm' = `0-100nm`- `0-12nm`)
# date Ship `0-100nm` `0-12nm` `12-100nm`
# 1 2018-04-01 Cargo(7X) 5 2 3
# 2 2018-04-01 Tanker(8X) 0 0 0
# 3 2018-04-02 Cargo(7X) 4 0 4
# 4 2018-04-02 Tanker(8X) 3 0 3
# 5 2018-04-03 Cargo(7X) 7 2 5
# 6 2018-04-03 Tanker(8X) 1 0 1
# 7 2018-04-04 Cargo(7X) 6 2 4
# 8 2018-04-04 Tanker(8X) 0 0 0
# 9 2018-04-05 Cargo(7X) 7 2 5
# 10 2018-04-05 Tanker(8X) 1 0 1
# 11 2018-04-06 Cargo(7X) 4 3 1
# 12 2018-04-06 Tanker(8X) 0 0 0
如果我理解你的问题,你应该能够使用dplyr
得到它。以下示例中的diff
字段:
library(dplyr)
df %>%
mutate(Total = `Passenger(6X)` + `Cargo(7X)` + `Tanker(8X)` + `Otherb`) %>%
group_by(date) %>%
mutate(diff = ifelse(row_number() == 1, Total, Total - lag(Total)))
date `Passenger(6X)` `Cargo(7X)` `Tanker(8X)` Otherb DOS Total diff
<date> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl>
1 2018-04-01 0 2 0 0 0-12nm 2 2
2 2018-04-02 0 0 0 0 0-12nm 0 0
3 2018-04-03 0 2 0 0 0-12nm 2 2
4 2018-04-04 0 2 0 0 0-12nm 2 2
5 2018-04-05 0 2 0 0 0-12nm 2 2
6 2018-04-06 0 3 0 0 0-12nm 3 3
7 2018-04-01 0 5 0 0 0-100nm 5 3
8 2018-04-02 0 4 3 0 0-100nm 7 7
9 2018-04-03 0 7 1 0 0-100nm 8 6
10 2018-04-04 0 6 0 0 0-100nm 6 4
11 2018-04-05 0 7 1 0 0-100nm 8 6
12 2018-04-06 0 4 0 0 0-100nm 4 1