为什么我不能将年龄组重新编码到另一个年龄组前瞻库中？

Question

我正在尝试最后几个小时，以了解为什么我不能将另一个年龄组的年龄组重新分组？我正在使用R中的forecats库进行此操作。

这里是数据：

data <-  structure(list(`Country code` = c(900, 900, 900, 900, 900, 900, 
    900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 
    900, 900), Type = c("World", "World", "World", "World", "World", 
    "World", "World", "World", "World", "World", "World", "World", 
    "World", "World", "World", "World", "World", "World", "World", 
    "World", "World"), `Parent code` = c(0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), year = c(2020, 2020, 
    2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 
    2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020), age_grps = c("0-4", 
    "05-Sep", "Oct-14", "15-19", "20-24", "25-29", "30-34", "35-39", 
    "40-44", "45-49", "50-54", "55-59", "60-64", "65-69", "70-74", 
    "75-79", "80-84", "85-89", "90-94", "95-99", "100+"), value = c("  677 942", 
    "  664 439", "  641 267", "  612 196", "  597 388", "  594 692", 
    "  605 531", "  544 819", "  493 789", "  479 366", "  445 773", 
    "  387 849", "  322 142", "  269 644", "  188 677", "  123 782", 
    "  81 930", "  42 186", "  16 680", "  4 134", "   573"
    ), age_groups = structure(c(1L, 2L, 21L, 4L, 5L, 6L, 7L, 8L, 
    9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 3L
    ), .Label = c("0-4", "0-9", "100+", "15-19", "20-24", "25-29", 
    "30-34", "35-39", "40-44", "45-49", "50-54", "55-59", "60-64", 
    "65-69", "70-74", "75-79", "80-84", "85-89", "90-94", "95-99", 
    "10-14"), class = "factor")), row.names = c(NA, -21L), class = c("tbl_df", 
    "tbl", "data.frame"))

这是重新分类：

age_levels <- c("0-4" = "0-19",
                      "5-9" = "0-19",
                      "10-14" = "0-19",
                      "15-19" = "0-19",
                      "20-24" = "20-39",
                      "25-29" = "20-39",
                      "30-34" = "20-39",
                      "35-39" = "20-39",
                      "40-44" = "40-59",
                      "45-49" = "40-59",
                      "50-54" = "40-59",
                      "55-59" = "40-59",
                      "65+" = "60-64",
                      "65+" = "65-69",
                      "65+" = "70-74",
                      "65+" = "75-79",
                      "65+" = "80-84",
                      "65+" = "85-89",
                      "65+" = "90-94",
                      "65+" = "95-99",
                      "65+" = "100+")

这是我正在使用的代码：

data_rec <- data %>%
  dplyr::mutate(age_recoded_band = forcats::fct_recode(age_groups, !!!age_levels))