我有一個這樣的資料集：
ID color1 color2 color3 shape1 shape2 size
55 red blue NA circle triangle small
67 yellow NA NA triangle NA medium
83 blue yellow NA circle NA large
78 red yellow blue square circle large
43 green NA NA square circle small
29 yellow green NA circle triangle medium
我想創建一個資料框，其中包含每個變數的頻率和百分比，但我遇到了麻煩，因為在某些情況下同一變數有多個列。
Variable Level Freq Percent
color blue 3 27.27
red 2 18.18
yellow 4 36.36
green 2 18.18
total 11 100.00
shape circle 5 50.0
triangle 3 30.0
square 2 20.0
total 10 100.0
size small 2 33.3
medium 2 33.3
large 2 33.3
total 6 100.0
我相信我需要將這些變數轉換為 long，然后使用匯總/變異來獲取頻率，但我似乎無法弄清楚。任何幫助是極大的贊賞。
uj5u.com熱心網友回復：
您可以使用tidyverse包將資料轉換為長格式，然后匯總所需的統計資訊。
library(tidyverse)
df |>
# Transform all columns into a long format
pivot_longer(cols = -ID,
names_pattern = "([A-z] )",
names_to = c("variable")) |>
# Drop NA entries
drop_na(value) |>
# Group by variable
group_by(variable) |>
# Count
count(value) |>
# Calculate percentage as n / sum of n by variable
mutate(perc = 100* n / sum(n))
# A tibble: 10 x 4
# Groups: variable [3]
# variable value n perc
# <chr> <chr> <int> <dbl>
# 1 color blue 3 27.3
# 2 color green 2 18.2
# 3 color red 2 18.2
# 4 color yellow 4 36.4
# 5 shape circle 5 50
# 6 shape square 2 20
# 7 shape triangle 3 30
# 8 size large 2 33.3
# 9 size medium 2 33.3
#10 size small 2 33.3
uj5u.com熱心網友回復：
組合并添加到：
在 R 中合并多個頻率表
為堆疊頻率表中的每個組添加一列總計 n
library(dplyr)
library(tidyr)
library(janitor)
options(digits = 3)
df %>%
pivot_longer(
-ID,
names_to = "Variable",
values_to = "Level"
) %>%
mutate(Variable = str_extract(Variable, '[A-Za-z]*')) %>%
group_by(Variable, Level) %>%
count(Level, name = "Freq") %>%
na.omit() %>%
group_by(Variable) %>%
mutate(Percent = Freq/sum(Freq)*100) %>%
group_split() %>%
adorn_totals() %>%
bind_rows() %>%
mutate(Level = ifelse(Level == last(Level), last(Variable), Level)) %>%
mutate(Variable = ifelse(duplicated(Variable) |
Variable == "Total", NA, Variable))
Variable Level Freq Percent
color blue 3 27.3
<NA> green 2 18.2
<NA> red 2 18.2
<NA> yellow 4 36.4
<NA> Total 11 100.0
shape circle 5 50.0
<NA> square 2 20.0
<NA> triangle 3 30.0
<NA> Total 10 100.0
size large 2 33.3
<NA> medium 2 33.3
<NA> small 2 33.3
<NA> Total 6 100.0
uj5u.com熱心網友回復：
嘗試這種matrix在list在基礎R
uniq <- unique( sub( "[0-9]","", colnames(dat[,-1]) ) )
uniq
[1] "color" "shape" "size"
sapply( uniq, function(x){ tbl <- table( unlist( dat[,grep( x, colnames(dat) )] ) );
rbind( cbind( Percent=round( tbl/sum(tbl)*100, digits=2 ), Freq=tbl ),
cbind( sum(tbl/sum(tbl)*100), sum(tbl) ) ) } )
$color
Percent Freq
blue 27.27 3
green 18.18 2
red 18.18 2
yellow 36.36 4
100.00 11
$shape
Percent Freq
circle 50 5
square 20 2
triangle 30 3
100 10
$size
Percent Freq
large 33.33 2
medium 33.33 2
small 33.33 2
100.00 6
資料
dat <- structure(list(ID = c(55L, 67L, 83L, 78L, 43L, 29L), color1 = c("red",
"yellow", "blue", "red", "green", "yellow"), color2 = c("blue",
NA, "yellow", "yellow", NA, "green"), color3 = c(NA, NA, NA,
"blue", NA, NA), shape1 = c("circle", "triangle", "circle", "square",
"square", "circle"), shape2 = c("triangle", NA, NA, "circle",
"circle", "triangle"), size = c("small", "medium", "large", "large",
"small", "medium")), class = "data.frame", row.names = c(NA,
-6L))
轉載請註明出處，本文鏈接：https://www.uj5u.com/qukuanlian/383141.html
標籤：r
上一篇：根據最高和最低列值過濾行