如何在R中随机选择区和该区中的村庄？

Question

我有一个数据集，其中包含有关地区代码和名称、该地区街区的代码和名称以及该街区中村庄的代码和名称的信息。

基于此，我想创建一个数据集，从该地区随机选择一个街区，并随机选取该选定街区中的 10 个村庄。

我尝试过使用示例函数和 RandomizeR 包，但可以让它工作。

I 数据集样本 (df)：

structure(list(district_code = c(1701L, 1701L, 1701L, 1701L, 
1701L, 1701L, 1701L, 1701L, 1701L, 1701L, 1701L, 1701L), district_name = c("morena", 
"morena", "morena", "morena", "morena", "morena", "morena", "morena", 
"morena", "morena", "morena", "morena"), block_code = c(1701001L, 
1701001L, 1701001L, 1701001L, 1701001L, 1701001L, 1701001L, 1701001L, 
1701001L, 1701001L, 1701001L, 1701001L), block_name = c("ambah", 
"ambah", "ambah", "ambah", "ambah", "ambah", "ambah", "ambah", 
"ambah", "ambah", "ambah", "ambah"), village_code = 1701001001:1701001012, 
    village_name = c("badfara", "bichola", "bhandauli", "lallubasai", 
    "kakarari", "rithona", "goonjh", "malbasai", "aroli", "khirenta", 
    "dandoli", "beelpur")), row.names = c(NA, 12L), class = "data.frame")

第二个样本 (df1)

structure(list(district_code = c(3424L, 3424L, 3424L, 3424L, 
3424L, 3424L, 3424L, 3424L, 3401L, 3401L, 3401L, 3401L, 3401L, 
3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L), district_name = c("khunti", 
"khunti", "khunti", "khunti", "khunti", "khunti", "khunti", "khunti", 
"ranchi", "ranchi", "ranchi", "ranchi", "ranchi", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga"), block_code = c(3401020L, 3401020L, 
3401020L, 3401020L, 3401020L, 3401020L, 3401020L, 3401020L, 3401024L, 
3401024L, 3401024L, 3401024L, 3401024L, 3402001L, 3402001L, 3402001L, 
3402001L, 3402001L, 3402001L, 3402001L, 3402001L), block_name = c("torpa", 
"torpa", "torpa", "torpa", "torpa", "torpa", "torpa", "torpa", 
"khelari", "khelari", "khelari", "khelari", "khelari", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga"), panchayat_code = c(3401020009, 3401020010, 
3401020011, 3401020012, 3401020013, 3401020014, 3401020015, 3401020016, 
3401024001, 3401024002, 3401024003, 3401024004, 3401024005, 3402001001, 
3402001002, 3402001003, 3402001004, 3402001005, 3402001006, 3402001007, 
3402001008), panchayat_name = c("marcha", "okra", "sundari", 
"tapkara", "torpa east", "torpa west", "ukrimari", "urikela", 
"churi east", "churi middle", "churi north", "churi south", "churi west", 
"hesal", "hirhi", "manho", "jori", "nigni", "juriya", "harmu", 
"rampur")), row.names = 379:399, class = "data.frame")
> dput(jk_subset[379:409,])
structure(list(district_code = c(3424L, 3424L, 3424L, 3424L, 
3424L, 3424L, 3424L, 3424L, 3401L, 3401L, 3401L, 3401L, 3401L, 
3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 
3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L, 3402L
), district_name = c("khunti", "khunti", "khunti", "khunti", 
"khunti", "khunti", "khunti", "khunti", "ranchi", "ranchi", "ranchi", 
"ranchi", "ranchi", "lohardaga", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "lohardaga"), block_code = c(3401020L, 
3401020L, 3401020L, 3401020L, 3401020L, 3401020L, 3401020L, 3401020L, 
3401024L, 3401024L, 3401024L, 3401024L, 3401024L, 3402001L, 3402001L, 
3402001L, 3402001L, 3402001L, 3402001L, 3402001L, 3402001L, 3402001L, 
3402001L, 3402001L, 3402006L, 3402001L, 3402007L, 3402007L, 3402007L, 
3402002L, 3402002L), block_name = c("torpa", "torpa", "torpa", 
"torpa", "torpa", "torpa", "torpa", "torpa", "khelari", "khelari", 
"khelari", "khelari", "khelari", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "lohardaga", "lohardaga", 
"lohardaga", "lohardaga", "lohardaga", "kairo", "lohardaga", 
"peshrar", "peshrar", "peshrar", "kisko", "kisko"), village_code = c(3401020009, 
3401020010, 3401020011, 3401020012, 3401020013, 3401020014, 3401020015, 
3401020016, 3401024001, 3401024002, 3401024003, 3401024004, 3401024005, 
3402001001, 3402001002, 3402001003, 3402001004, 3402001005, 3402001006, 
3402001007, 3402001008, 3402001009, 3402001010, 3402001011, 3402001012, 
3402001013, 3402002001, 3402002002, 3402002003, 3402002004, 3402002005
), village_name = c("marcha", "okra", "sundari", "tapkara", 
"torpa east", "torpa west", "ukrimari", "urikela", "churi east", 
"churi middle", "churi north", "churi south", "churi west", "hesal", 
"hirhi", "manho", "jori", "nigni", "juriya", "harmu", "rampur", 
"bagha", "arkosa", "tigra", "guri", "bhatdhijri", "siram", "peshrar", 
"rorad", "devdaria", "pakhar")), row.names = 379:409, class = "data.frame")

使用代码后的数据集示例：

3404L, 3405L, 3406L, 3407L, 3408L, 3409L, 3410L, 3411L), district_name = c("khunti", 
"ranchi", "lohardaga", "gumla", "simdega", "palamu", "latehar", 
"garhwa", "west singhbhum", "saraikela kharsawan", "east singhbum", 
"dumka"), block_code = c(3401009L, 3401013L, 3402005L, 3403009L, 
3404002L, 3405018L, 3406006L, 3407009L, 3408005L, 3409006L, 3410005L, 
3411009L), block_name = c("khunti", "namkum", "bhandra", "basia", 
"bolba", "tarhasi", "garu", "bhandaria", "tantnagar", "ichagarh", 
"musabani", "masaliya"), village_code = c(3401009002, 3401013020, 
3402005002, 3403009008, 3404002002, 3405006012, 3406006008, 3407009002, 
3408005001, 3409006012, 3410005011, 3411009001), village_name = c("bhandra", 
"sithiyo", "bhandra", "mamarla", "kadopani", "manjhauli 2", "ghasitola", 
"bhandaria", "angardiha", "dewaltand", "ichra (north)", "aamgachi"
)), row.names = c(NA, -12L), class = c("tbl_df", "tbl", "data.frame"
))

Answer 1

您的示例并不真正适合提供解决方案，因为它仅包含一个区/街区。

但你可以这样做：

df %>%
  group_by(district_code) %>%
  filter(block_code == ifelse(length(unique(block_code)) == 1, block_code, sample(unique(block_code), size = 1))) %>%
  filter(village_code %in% ifelse(length(unique(village_code)) == 1, village_code, sample(unique(village_code), size = min(10, length(unique(village_code))), replace = FALSE))) %>%
  ungroup()

注意：我并不完全确定你想要在哪个级别进行抽样，所以在这里我选择每个区一个街区，然后从该街区选择 10 个村庄。因此，您最终会从每个区随机选择的街区中获得 10 个村庄。