Question

我想重塑我的数据，但由于从宽到长不完全精确，所以无法弄清楚。

这是我的数据样本，按年龄和性别分类人口

data <- structure(list(`2010 - Both Sexes - 0` = 163753, `2010 - Male - 0` = 83878, `2010 - Female - 0` = 79875, `2011 - Both Sexes - 0` = 161923, 
                       `2011 - Male - 0` = 83134, `2011 - Female - 0` = 78789, `2010 - Both Sexes - 1` = 163043, 
                       `2010 - Male - 1` = 83174, `2010 - Female - 1` = 79869, `2011 - Both Sexes - 1` = 163342, 
                       `2011 - Male - 1` = 83472, `2011 - Female - 1` = 79870), row.names = c(NA, 
                         -1L), class = c("tbl_df", "tbl", "data.frame"))

我想要的数据集如下所示：

 age  2010 - Both Sexes   2010 - Male   2010 - Female  2011 - Both Sexes 2011 - Male   2011 - Female ...
  0                                     
  1

                 ...

有人可以帮忙吗？谢谢。

Answer 1

我不知道您为什么会想要这种格式，但是您可以像这样使用tidyr来做到这一点：

gather所有列分为姓和名的列；
separate通过将第二个age拆分为其他两个-；
spread取消总体值。

library(tidyverse)
data <- structure(list(`2010 - Both Sexes - 0` = 163753, `2010 - Male - 0` = 83878, `2010 - Female - 0` = 79875, `2011 - Both Sexes - 0` = 161923, `2011 - Male - 0` = 83134, `2011 - Female - 0` = 78789, `2010 - Both Sexes - 1` = 163043, `2010 - Male - 1` = 83174, `2010 - Female - 1` = 79869, `2011 - Both Sexes - 1` = 163342, `2011 - Male - 1` = 83472, `2011 - Female - 1` = 79870), row.names = c(NA, -1L), class = c("tbl_df", "tbl", "data.frame"))

data %>%
  gather(year_sex_age, population) %>%
  separate(year_sex_age, c("year_sex", "age"), sep = " - (?=0|1)") %>%
  spread(year_sex, population)
#> # A tibble: 2 x 7
#>   age   `2010 - Both Se~ `2010 - Female` `2010 - Male` `2011 - Both Se~
#>   <chr>            <dbl>           <dbl>         <dbl>            <dbl>
#> 1 0               163753           79875         83878           161923
#> 2 1               163043           79869         83174           163342
#> # ... with 2 more variables: `2011 - Female` <dbl>, `2011 - Male` <dbl>

由reprex package（v0.2.0）于2018-08-01创建。

R重建数据

1 个答案: