英文:
I Want to Group IDs According to Eco_Status Using R
问题
我想要另一个数据框，其中包含四个Eco_Status作为列，并且将每个ID按照它们在每个Eco_Status下出现的情况分组。
给定上述数据框df，我想要一个包含poor、average、rich和billionaire作为它们状态的ID的向量。
英文:
I want another data frame that has the four(4) Eco_Status as column and group each ID as each occurs under each Eco_Status
# group ID_numbers according to their respective status
df <- read.table(text =
"ID Pof_Exp Eco_Status Gender
31304 2 poor male
31310 4 poor female
31307 6 rich male
31302 8 average male
31301 10 billionaire male
31308 2 poor female
31316 4 poor male
31317 6 rich male
31312 8 average female
31306 10 average female
31314 2 poor female
31311 4 average male
31305 6 rich male
31303 8 average male
31309 10 average female
31324 2 poor male
31320 4 poor female
31327 6 average male
31322 8 average female
31321 10 billionaire male",
header = TRUE)
Given the above data frame df, I want a vector of ID having poor, average, rich, and billionaire as their status.
答案1
得分: 2
这是另一个可能的解决方案：
df %>%
select(-c(Pof_Exp, Gender)) %>%
group_by(Eco_Status) %>%
mutate(row = row_number()) %>%
tidyr::pivot_wider(names_from = Eco_Status, values_from = ID) %>%
select(-row)
这将产生以下结果：
poor rich average billionaire
<int> <int> <int> <int>
1 31304 31307 31302 31301
2 31310 31317 31312 31321
3 31308 31305 31306 NA
4 31316 NA 31311 NA
5 31314 NA 31303 NA
6 31324 NA 31309 NA
7 31320 NA 31327 NA
8 NA NA 31322 NA
英文:
here is another possible solution:
df %>% select(-c(Pof_Exp, Gender)) %>% group_by(Eco_Status) %>%
mutate(row = row_number()) %>%tidyr::pivot_wider(names_from = Eco_Status, values_from = ID) %>%
select(-row)
which gives:
poor rich average billionaire
<int> <int> <int> <int>
1 31304 31307 31302 31301
2 31310 31317 31312 31321
3 31308 31305 31306 NA
4 31316 NA 31311 NA
5 31314 NA 31303 NA
6 31324 NA 31309 NA
7 31320 NA 31327 NA
8 NA NA 31322 NA
答案2
得分: 1
像这样吗？
df %>%
group_by(Eco_Status) %>%
summarise(ID = list(ID))
Eco_Status ID
1 average 31302, 31312, 31306, 31311, 31303, 31309, 31327, 31322
2 billionaire 31301, 31321
3 poor 31304, 31310, 31308, 31316, 31314, 31324, 31320
4 rich 31307, 31317, 31305
英文:
Something like this?
df %>%
group_by(Eco_Status) %>%
summarise(ID = list(ID))
Eco_Status ID
1 average 31302, 31312, 31306, 31311, 31303, 31309, 31327, 31322
2 billionaire 31301, 31321
3 poor 31304, 31310, 31308, 31316, 31314, 31324, 31320
4 rich 31307, 31317, 31305
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