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Legal Studies如何使用 R 中的 dplyr 建立相對頻次表？
相對頻次是某項事物佔總數的比例。例如，如果我們有 5 根香蕉、6 個番石榴和 10 個石榴，那麼香蕉的相對頻次就是 5 除以 5、6 和 10 的總和，即 21，因此它也可以稱為成比例頻次。
示例 1
考慮以下資料幀 −
set.seed(21) x<−sample(LETTERS[1:4],20,replace=TRUE) Ratings<−sample(1:50,20) df1<−data.frame(x,Ratings) df1
輸出
x Ratings 1 C 44 2 A 29 3 C 14 4 A 10 5 B 46 6 C 1 7 D 47 8 A 8 9 C 23 10 C 7 11 D 50 12 B 31 13 B 34 14 B 3 15 D 48 16 B 33 17 C 45 18 B 9 19 B 40 20 C 21
載入 dplyr 包 −
library(dplyr)
尋找 x 中值的相對頻次表 −
df1%>%group_by(x)%>%summarise(n=n())%>%mutate(freq=n/sum(n)) `summarise()` ungrouping output (override with `.groups` argument) # A tibble: 4 x 3
輸出
x n freq <chr> <int> <dbl> 1 A 3 0.15 2 B 7 0.35 3 C 7 0.35 4 D 3 0.15 Warning message: `...` is not empty. We detected these problematic arguments: * `needs_dots` These dots only exist to allow future extensions and should be empty. Did you misspecify an argument?
注意 − 不要擔心此警告訊息，因為我們的問題已正確解決，且該警告與此無關。
示例 2
y<−sample(c("Male","Female"),20,replace=TRUE)
Salary<−sample(20000:50000,20)
df2<−data.frame(y,Salary)
df2輸出
y Salary 1 Female 40907 2 Female 47697 3 Male 49419 4 Female 23818 5 Male 21585 6 Male 22276 7 Female 21856 8 Male 22092 9 Male 27892 10 Female 47655 11 Male 34933 12 Female 48027 13 Female 48179 14 Male 21460 15 Male 24233 16 Female 43762 17 Female 22369 18 Female 47206 19 Male 34972 20 Female 30222
尋找 y 中性別的相對頻次 −
df2%>%group_by(y)%>%summarise(n=n())%>%mutate(freq=n/sum(n)) `summarise()` ungrouping output (override with `.groups` argument) # A tibble: 2 x 3
輸出
y n freq <chr> <int> <dbl> 1 Female 11 0.55 2 Male 9 0.45 Warning message: `...` is not empty. We detected these problematic arguments: * `needs_dots` These dots only exist to allow future extensions and should be empty. Did you misspecify an argument?
更新於：07-11-2020
566 次瀏覽
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