Reshape ()和modify_shape()

Question

df <- data.frame(
code1 = c ("ZAZ","ZAZ","ZAZ","ZAZ","ZAZ","ZAZ","JOZ","JOZ","JOZ","JOZ","JOZ","JOZ","TSV","TSV"), 
code2 = c("NAN","NAN","NAN","NAN","NAN","NAN","NAN","NAN","NAN","NAN","NAN","NAN","TSA","TSA"),
start = c("Date1.1","Date1.1","Date1.3","Date1.3","Date1.5","Date1.5","Date3.1","Date3.1","Date3.3","Date3.3","Date3.5","Date3.5","Date 5.1","Date 5.1"),
end = c("Date2.1","Date2.1","Date2.3","Date2.3","Date2.5","Date2.5","Date4.1","Date4.1","Date4.3","Date4.3","Date4.5","Date4.5","Date6.1","Date6.1"),
price = c(1,2,3,4,5,6,1,2,3,4,5,6,1,2))

我正在努力实现：

​

到目前为止，我已经做了：

df <- df %>% 
group_by(code1, code2,start,end) %>% 
slice_min(price) #%>% 
group_modify()
df <- df[order(df$price),]

图中解释得很好，但简单地说：

• 按code1、code2、start、end和选择最小的价格对每个
• 重新发送开始、结束、价格到不同的列(最大3开始、结束、每键价格code1、code2
• )--我知道这可以在

内部完成，但不确定是如何实现的。

任何帮助都是非常感谢的！布赖恩

Answer 1

下面是使用dplyr和tidyr库的一种方法。

每个组( price.

• Create、code2、start和end)的
• 计算code1和code2的一个索引列的最小值。这是为了将start、end和price命名为start_1、start_2等。
• 使用start_1以宽格式获取数据。

library(dplyr)
library(tidyr)

df %>%
  group_by(code1, code2, start, end) %>%
  summarise(price = min(price, na.rm = TRUE)) %>%
  group_by(code1, code2) %>%
  mutate(index = row_number()) %>%
  ungroup() %>%
  pivot_wider(names_from = index, values_from = c(start, end, price),
              names_vary = "slowest")
  

#  code1 code2 start_1  end_1   price_1 start_2 end_2   price_2 start_3 end_3   price_3
#  <chr> <chr> <chr>    <chr>     <dbl> <chr>   <chr>     <dbl> <chr>   <chr>     <dbl>
#1 JOZ   NAN   Date3.1  Date4.1       1 Date3.3 Date4.3       3 Date3.5 Date4.5       5
#2 TSV   TSA   Date 5.1 Date6.1       1 NA      NA           NA NA      NA           NA
#3 ZAZ   NAN   Date1.1  Date2.1       1 Date1.3 Date2.3       3 Date1.5 Date2.5       5

注意，names_vary = "slowest"允许有有序的列(start_1，end_1，price_1.而不是start_1，start_2 .，end_1，end_2。(等等)

Answer 2

我想你可以试试aggregate + reshape + ave (都来自R基)。

reshape(
  transform(
    aggregate(price ~ ., df, min),
    id = ave(seq_along(price), code1, code2, FUN = seq_along)
  ),
  direction = "wide",
  idvar = c("code1", "code2"),
  timevar = "id"
)

这给

  code1 code2 start.1   end.1 price.1 start.2   end.2 price.2 start.3   end.3
1   ZAZ   NAN Date1.1 Date2.1       1 Date1.3 Date2.3       3 Date1.5 Date2.5
4   JOZ   NAN Date3.1 Date4.1       1 Date3.3 Date4.3       3 Date3.5 Date4.5
7   TSV   TSA Date5.1 Date6.1       1    <NA>    <NA>      NA    <NA>    <NA>
  price.3
1       5
4       5
7      NA