英文:
How could one branch multiple variables under another variable in R?
问题
我正在尝试按一组变量将我的观察结果分组，这些变量最终会归属于最后一组变量。这是我的示例数据：
国家 姓名 民族 党派
阿富汗 约翰 普什图人 X党
阿富汗 奥利弗 普什图人 Y党
阿富汗 布拉德 塔吉克人 X党
阿富汗 查德 哈扎拉人 X党
波斯尼亚 维尔京 塞尔维亚人 P党
波斯尼亚 玛丽 塞尔维亚人 P党
波斯尼亚 耶稣 克罗地亚人 C党
我要做的是在每个党派下创建所有现有民族的集合，并计算在每个党派下有多少人属于每个民族，还要考虑国家，结果应该如下所示：
国家 党派 民族 人数
阿富汗 X党 普什图人 1
阿富汗 X党 塔吉克人 1
阿富汗 X党 哈扎拉人 1
阿富汗 Y党 普什图人 1
阿富汗 Y党 塔吉克人 0
阿富汗 Y党 哈扎拉人 0
波斯尼亚 P党 塞尔维亚人 2
波斯尼亚 P党 克罗地亚人 0
波斯尼亚 C党 塞尔维亚人 0
波斯尼亚 C党 克罗地亚人 1
到目前为止，我尝试了 group_by 和 aggregate 函数，但没有成功。
英文:
I'm trying to group my observations by a set of variables under another set of variables which is, finally, under a last set of variables. Here's what I have for example:
country name ethnicity party
Afghanistan john Pashtun X Party
Afghanistan oliver Pashtun Y Party
Afghanistan brad Tajik X Party
Afghanistan chad Hazara X Party
Bosnia virgin Serb P Party
Bosnia mary Serb P Party
Bosnia jesus Croat C Party
What I'm going for should create the set of all existing ethnicities under each party and count how many persons are under each ethnicity in a party, within a country and look something like:
country party ethnicity count
Afghanistan X Party Pashtun 1
Afghanistan X Party Tajik 1
Afghanistan X Party Hazara 1
Afghanistan Y Party Pashtun 1
Afghanistan Y Party Tajik 0
Afghanistan Y Party Hazara 0
Bosnia P Party Serb 2
Bosnia P Party Croat 0
Bosnia C Party Serb 0
Bosnia C Party Croat 1
So far I've tried the functions group_by and aggregate to no avail.
答案1
得分: 1
这是一个非常简单的操作，请阅读这本书 https://r4ds.had.co.nz/
library(data.table)
library(tidyverse)
df_example <- fread("country name ethnicity party coolness
Afghanistan john Pashtun X_Party cool
Afghanistan oliver Pashtun Y_Party not_cool
Afghanistan brad Tajik X_Party cool
Afghanistan chad Hazara X_Party not_cool
Bosnia virgin Serb P_Party cool
Bosnia mary Serb P_Party cool
Bosnia jesus Croat C_Party not_cool" ,
header = TRUE)
df_example %>%
group_by(country,ethnicity,party) %>%
add_tally() %>%
select(-name) %>%
distinct()
英文:
this is a really simply operation, please read this book https://r4ds.had.co.nz/
library(data.table)
library(tidyverse)
df_example <- fread("country name ethnicity party coolness
Afghanistan john Pashtun X_Party cool
Afghanistan oliver Pashtun Y_Party not_cool
Afghanistan brad Tajik X_Party cool
Afghanistan chad Hazara X_Party not_cool
Bosnia virgin Serb P_Party cool
Bosnia mary Serb P_Party cool
Bosnia jesus Croat C_Party not_cool" ,
header = TRUE)
df_example %>%
group_by(country,ethnicity,party) %>%
add_tally() %>%
select(-name) %>% # Some stuff that you don't want
distinct()
答案2
得分: 1
你可以使用 dplyr 和 tidyr：
df %>%
count(!!!select(., -name)) %>%
group_by(country) %>%
complete(ethnicity, nesting(party), fill = list(n = 0))
country ethnicity party n
<chr> <chr> <fct> <dbl>
1 Afghanistan Hazara X Party 1
2 Afghanistan Hazara Y Party 0
3 Afghanistan Pashtun X Party 1
4 Afghanistan Pashtun Y Party 1
5 Afghanistan Tajik X Party 1
6 Afghanistan Tajik Y Party 0
7 Bosnia Croat C Party 1
8 Bosnia Croat P Party 0
9 Bosnia Serb C Party 0
10 Bosnia Serb P Party 2
英文:
You can use dplyr and tidyr:
df %>%
count(!!!select(., -name)) %>%
group_by(country) %>%
complete(ethnicity, nesting(party), fill = list(n = 0))
country ethnicity party n
<chr> <chr> <fct> <dbl>
1 Afghanistan Hazara X Party 1
2 Afghanistan Hazara Y Party 0
3 Afghanistan Pashtun X Party 1
4 Afghanistan Pashtun Y Party 1
5 Afghanistan Tajik X Party 1
6 Afghanistan Tajik Y Party 0
7 Bosnia Croat C Party 1
8 Bosnia Croat P Party 0
9 Bosnia Serb C Party 0
10 Bosnia Serb P Party 2
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