英文:
How to get stats from a dataframe?
问题
我有点生疏R语言，如果你能帮助我，我会很感激。
我有一个数据框，我需要从中获取一些统计信息。这个数据框（以更简单的方式）看起来像这样：
df <- data.frame(tech=c("Leonardo", "Leonardo", "Leonardo", "John", "John", "John", "Will", "Will", "Will", "Bob"),
type=c("V", "P", "V", "V", "P", "V", "V", "P", "V", "V"),
breed=c("A", "A", "A", "B", "B", "B", "C", "C", "A", "B"),
central=c("J", "J", "K", "J", "K", "J", "K", "K", "K", "J"))
我需要在另一个数据框中获取每位技术人员按"type"的百分比。然后，另一个数据框包含每位技术人员按品种("breed")的"type"的百分比。（例如：如果一位技术人员只有一个类型（要么V，要么P），则反映为100%）
我看过其他主题，其中用户想要获取类似的信息(在R中按子组百分比汇总)，但他们有一个数值值来获取这个百分比。在我的情况下，我有V或P。我想象思维方式是相同的，但我尝试了其他帖子上建议的解决方案，对我的情况不起作用。
有没有一种简单的方法可以做到这一点？我感谢你的帮助。
英文:
I am a little bit rusty in R, and appreciate if you could help me.
I have a dataframe that I need to get some stats from it. The data frame (in a simpler way) looks like this:
df <- data.frame(tech=c("Leonardo", "Leonardo", "Leonardo", "John", "John", "John", "Will", "Will", "Will", "Bob"),
type=c("V", "P", "V", "V", "P", "V", "V", "P", "V", "V"),
breed=c("A", "A", "A", "B", "B", "B", "C", "C", "A", "B"),
central=c("J", "J", "K", "J", "K", "J", "K", "K", "K", "J")
I need to get the percentage of "type" by each technician in another dataframe. And then other daframe containg the percentage of "type" by each technician by breed. (ex: If a technician has only one type (either V or P), it would reflect in 100%)
I have seen other topics where the user wanted to get similar information (Summarizing by subgroup percentage in R) but they had a numerical value to get this percentage. In my case, I have V or P. I imagine it's the same way of thinking but I tried the suggested solution on the other post and it's not working in my case.
Is there a simple way of doing this? I appreciate your help
答案1
得分: 1
如果我理解你的问题正确，这是我使用dplyr来执行的方法：
df %>%
dplyr::group_by(tech, breed) %>%
dplyr::summarize(pct_v = sum(type == "V")/dplyr::n() * 100,
pct_p = sum(type == "P")/dplyr::n() * 100)
英文:
If I'm understanding your question right, this is how I'd do it using dplyr:
df |>
dplyr::group_by(tech, breed) |>
dplyr::summarize(pct_v = sum(type == "V")/dplyr::n() * 100,
pct_p = sum(type == "P")/dplyr::n() * 100)
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