Question

要在我的女性固定影响估计中包括各州的年度趋势，我想为每个州创建一个单独的变量，第一年的值为1，第二年的值为2，依此类推，对于第一年的值为0。其他所有州。我设法创建了一个满足所有这些要求的变量（在示例中为“ stateyear”），只是它只是所有州的一个变量（请参见示例）。是否有一种方法可以将每个变量按组（state_geocode_id）拆分为多个变量，并将除相应状态以外的所有其他状态都设置为0？

简化的数据集：

<!DOCTYPE html>
<html>
<head>
    <title>Rainbow</title>
    <meta charset="UTF-8" />
    <style>
        * { box-sizing: border-box; }

        .separate   { width: 100%; height: 10em; }
        .separate>* { width: 100%; height: 100%; margin-top: 1em; }

        .overlay   { width: 100%; height: 10em; filter: brightness(3); }
        .overlay>* { width: 100%; height: 100%; position: absolute; }
        .overlay>:nth-of-type(1) { opacity: 1; }
        .overlay>:nth-of-type(2) { opacity: .5; }
        .overlay>:nth-of-type(3) { opacity: .33; }
        .overlay>:nth-of-type(4) { opacity: .25; }

        .blue   { background: linear-gradient(
           90deg,                 rgb(0,0,256)  0%, rgb(0,0,256) 5%,  rgb(0,0,0) 20% ); }
        .green  { background: linear-gradient(
           90deg, rgb(0,0,0) 0%,  rgb(0,256,0) 25%, rgb(0,256,0) 35%, rgb(0,0,0) 55% ); }
        .red    { background: linear-gradient(
           90deg, rgb(0,0,0) 15%, rgb(256,0,0) 35%, rgb(256,0,0) 45%, rgb(0,0,0) 100% ); }
        .blue2  { background: linear-gradient(
           90deg, rgb(0,0,0) 65%, rgb(0,0,256) 95%, rgb(0,0,256) 100% ); }
    </style>
</head>
<body>
<h1>Rainbow</h1>
    <div class="overlay">
        <div class="blue"></div>
        <div class="green"></div>
        <div class="red"></div>
        <div class="blue2"></div>
    </div>
    <div class="separate">
        <div class="blue"></div>
        <div class="green"></div>
        <div class="red"></div>
        <div class="blue2"></div>
    </div>
</body>
</html>

添加“州年”变量：

d <- data.frame("100")
names(d) <- "state_geocode_id"
d$state_geocode_id <- as.character(d$state_geocode_id)
d <- rbind(d, "100", "100", "100", "101", "101", "101", "101", "102", "102", "102", "102")
d$municip <- c("1", "1", "2", "2", "3", "3", "4", "4", "5", "5", "6", "6")
d$year <- c("2000", "2001", "2000", "2001","2000", "2001", "2000", "2001", "2000", "2001", "2000", "2001")

Answer 1

喜欢吗？

library(tidyverse)

d %>% 
  group_by(state_geocode_id) %>% 
  #add a row counter and duplicate the state id
  mutate(row = row_number(), 
         state2 = state_geocode_id) %>% 
  #now spread by the duplicate state to get a column for each state
  spread(key = state2, value = row, fill = 0)

# A tibble: 12 x 6
# Groups:   state_geocode_id [4]
state_geocode_id year  `100` `101` `102` `103`
<chr>            <chr> <dbl> <dbl> <dbl> <dbl>
1 100              2000      1     0     0     0
2 100              2001      2     0     0     0
3 100              2002      3     0     0     0
4 101              2000      0     1     0     0
5 101              2001      0     2     0     0
6 101              2002      0     3     0     0
7 102              2000      0     0     1     0
8 102              2001      0     0     2     0
9 102              2002      0     0     3     0
10 103              2000      0     0     0     1
11 103              2001      0     0     0     2
12 103              2002      0     0     0     3

按组将一个变量分成多个变量

1 个答案: