将时间信息汇总到动态矩阵中

Question

我有一个像 df:

这样的数据框

id <- c("A", "A", "A", "A", "B", "B", "B", "C", "C", "D", "D", "E")
year <- c("2005", "2006", "2007", "2008", "2005", "2006", "2007", "2005", "2007", "2006", "2007", "2008")
value <- 1:12
df <- data.frame(id, year, value)

我想将 df 转换为矩阵 id_observed，其中列按年份计算首次观察到的 ID 的数量。 Rows 统计有多少个 id“存活”到连续的一年：

id_observed <- matrix(c(3,2,3,1,0,1,1,0,0,0,0,0,0,0,0,1), nrow = 4, ncol = 4)
#First observed id's (by columns), consecutive id's observations (by rows)
colnames(id_observed) <- c("2005", "2006", "2007", "2008")
rownames(id_observed) <- c("2005", "2006", "2007", "2008")
id_observed

同样的想法适用于从 value 中获取信息生成矩阵 value_observed。其中列按年份计算首次观察到的 id 的聚合值。 Rows统计“存活”到连续年份的ids的聚合值：

value_observed <- matrix(c(14,8,19,4,0,10,11,0,0,0,0,0,0,0,0,12), nrow = 4, ncol = 4)
#First observed value (by columns), consecutive value's observations (by rows)
colnames(value_observed) <- c("2005", "2006", "2007", "2008")
rownames(value_observed) <- c("2005", "2006", "2007", "2008")
value_observed

关于如何自动构建矩阵 id_observed 和 value_observed 的任何线索？

Answer 1

您可以创建这个函数，get_matrix()，它利用 tidyverse 方法循环独特的年份，为每一年创建数据，绑定行，然后旋转更宽

library(tidyverse)

get_matrix <- function(df, type=c("value","id")) {
  res = lapply(unique(df$year), function(y) {
    d = df %>% group_by(id) %>% filter(min(year)==y) %>% group_by(year)
    if(type == "value") d = summarize(d,n=sum(value))
    else d = summarize(d,n=n())
    d = mutate(d,y=y)
    if(nrow(d)==0) return(tibble(year=y, n=0, y=y)) else return(d)
  })
  bind_rows(res) %>% 
    pivot_wider(id_cols = year,names_from = y,values_from = n,values_fill = 0)    
}

用法

get_matrix(df, type="value")

输出

  year  `2005` `2006` `2007` `2008`
  <chr>  <dbl>  <dbl>  <dbl>  <dbl>
1 2005      14      0      0      0
2 2006       8     10      0      0
3 2007      19     11      0      0
4 2008       4      0      0     12

用法

get_matrix(df, type="id")

输出

  year  `2005` `2006` `2007` `2008`
  <chr>  <dbl>  <dbl>  <dbl>  <dbl>
1 2005       3      0      0      0
2 2006       2      1      0      0
3 2007       3      1      0      0
4 2008       1      0      0      1

更新：

data.table 选项

setDT(df)[, year:=as.integer(year)]
syears = unique(df$year)
df = df[, y:=min(year), by = id][, .SD[,.N, year], by=y]
dcast(
  rbind(df,data.table(y=setdiff(syears, unique(df$y)))[,`:=`(year=y,N=0)]),
  year~y, value.var="N"
)

输出：

    year  2005  2006  2007  2008
   <int> <num> <num> <num> <num>
1:  2005     3    NA    NA    NA
2:  2006     2     1    NA    NA
3:  2007     3     1     0    NA
4:  2008     1    NA    NA     1

将时间信息汇总到动态矩阵中

Summarize temporal information into a dynamic matrix

r

matrix

dplyr

tidyverse

summarize

更新：