重新安排每组

我有R的工作表，我有这样的数据：重新安排每组

data <- structure(list(Col1 = 1:9, Col2 = structure(c(2L, 2L, 2L, 1L, 
3L, 3L, 3L, 3L, 3L), .Label = c("Administrative ", "National", 
"Regional"), class = "factor"), Col3 = structure(c(NA, 3L, 4L, 
NA, 2L, 3L, 1L, 4L, 3L), .Label = c("bike", "boat", "car", "truck" 
), class = "factor"), Col4 = c(56L, 65L, 58L, 62L, 24L, 25L, 
120L, 89L, 468L), X = c(NA, NA, NA, NA, NA, NA, NA, NA, NA), 
    X.1 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA)), .Names = c("Col1", 
"Col2", "Col3", "Col4", "X", "X.1"), class = "data.frame", row.names = c(NA, 
-9L))

我想重新安排一下，看看有什么可以或NOR。输出看起来像这样：

result <- structure(list(Col1 = c(1L, 4L, 5L), Col2 = structure(c(2L, 1L, 
3L), .Label = c("Administrative ", "National", "Regional"), class = "factor"), 
    car = c(1L, 0L, 1L), truck = c(1L, 0L, 1L), boat = c(0L, 
    0L, 1L), bike = c(0L, 0L, 1L)), .Names = c("Col1", "Col2", 
"car", "truck", "boat", "bike"), class = "data.frame", row.names = c(NA, 
-3L))

我已经试过聚合，但我仍然远离结果。帮助将是

t <- aggregate(data$Col2, by=list(data$Col3), c)

欢迎来到帮助！

来源

2017-09-27 Floni

还请加入您正在使用的语言，使得它更容易找到帮助。 –

已编辑！这是在主题标题:) – Floni

我们可以使用dcast从data.table与length为fun.aggregate

library(data.table) 
dcast(setDT(data), Col2~ Col3, length)[, 1:5, with = FALSE]

来源

2017-09-27 07:04:51 akrun

好像是perfecly工作，谢谢！ – Floni

这里是一个dplyr解决方案，如果你有兴趣，虽然akrun的解决方案似乎更简洁：

library(tidyverse) 

result <- data %>% 
    group_by(Col2, Col3) %>% 
    summarise(tot = sum(Col4)) %>% 
    mutate(bool = if_else(tot > 0, 1, 0)) %>% 
    select(Col2, Col3, bool) %>% 
    spread(key = Col3, value = bool, fill = 0) %>% 
    select(-`<NA>`)

来源

2017-09-27 07:13:34 User632716

下面是使用一个想法基R，

#convert to character 
data[2:3] <- lapply(data[2:3], as.character) 

#get unique elements to tabulate 
i1 <- unique(data$Col3) 
i1 <- i1[!is.na(i1)] 


setNames(data.frame(do.call(rbind, lapply(split(data$Col3, data$Col2), function(i) 
              as.integer(match(i1, i, nomatch = 0) > 0)))), i1)

其给出，

   car truck boat bike 
Administrative 0  0 0 0 
National   1  1 0 0 
Regional   1  1 1 1

来源

2017-09-27 07:20:09 Sotos

下面是使用table和一些胁迫另一个基R法。

(table(data$Col2, data$Col3) > 0) + 0L 

        bike boat car truck 
    Administrative  0 0 0  0 
    National   0 0 1  1 
    Regional   1 1 1  1

table计数实例，为NAs返回0。然后，我们强制逻辑与> 0到值大于1，后回落至整数，+ 0L。

来源

2017-09-27 12:21:31 lmo

重新安排每组

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