是否可以按州年龄或12岁以上获得美国人口？我正在尝试使用tidycensus包，但我不确定如何限制计数以添加年龄限制。
library(tidycensus)
library(tidyverse)
census_api_key("MYKEY")
pop90 <- get_acs(geography = "state", variables = "B01003_001", year = 1990)
该特定变量"B01003-001"的"宇宙"是总人口，它没有比这更进一步的细分，因此您无法从"B01003-001"获得12+年龄，只能获得您当时从中抽取的整个州或县或地区的人口。
但是，您可以使用B01001和后缀_001到_049来提取所需的表的数据框，然后将它们相加。
或
您可以像上面一样提取整个人口并减去年龄(男性和女性都不在您的目标群体中，考虑到与其余生活相比，儿童年龄组的细分，工作量要少得多(
你会很难接受的一件事是获得 12+，因为你想要排除的最高分组是 10-14......这意味着你不能选择低于 12
所有种族按性别划分的一般年龄代码：
B01001_001 Total:
B01001_002 Male:
B01001_003 Male: Under 5 years
B01001_004 Male: 5 to 9 years
B01001_005 Male: 10 to 14 years
B01001_006 Male: 15 to 17 years
B01001_007 Male: 18 and 19 years
B01001_008 Male: 20 years
B01001_009 Male: 21 years
B01001_010 Male: 22 to 24 years
B01001_011 Male: 25 to 29 years
B01001_012 Male: 30 to 34 years
B01001_013 Male: 35 to 39 years
B01001_014 Male: 40 to 44 years
B01001_015 Male: 45 to 49 years
B01001_016 Male: 50 to 54 years
B01001_017 Male: 55 to 59 years
B01001_018 Male: 60 and 61 years
B01001_019 Male: 62 to 64 years
B01001_020 Male: 65 and 66 years
B01001_021 Male: 67 to 69 years
B01001_022 Male: 70 to 74 years
B01001_023 Male: 75 to 79 years
B01001_024 Male: 80 to 84 years
B01001_025 Male: 85 years and over
B01001_026 Female:
B01001_027 Female: Under 5 years
B01001_028 Female: 5 to 9 years
B01001_029 Female: 10 to 14 years
B01001_030 Female: 15 to 17 years
B01001_031 Female: 18 and 19 years
B01001_032 Female: 20 years
B01001_033 Female: 21 years
B01001_034 Female: 22 to 24 years
B01001_035 Female: 25 to 29 years
B01001_036 Female: 30 to 34 years
B01001_037 Female: 35 to 39 years
B01001_038 Female: 40 to 44 years
B01001_039 Female: 45 to 49 years
B01001_040 Female: 50 to 54 years
B01001_041 Female: 55 to 59 years
B01001_042 Female: 60 and 61 years
B01001_044 Female: 65 and 66 years
B01001_045 Female: 67 to 69 years
B01001_046 Female: 70 to 74 years
B01001_047 Female: 75 to 79 years
B01001_048 Female: 80 to 84 years
B01001_049 Female: 85 years and over
因此，您需要以某种方式调整模型或获取PUMS数据并根据自己的喜好进行聚合。