多列表示一个值时的频率表 (R)

Question

我有一个这样的数据集：

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

我想创建一个数据框，其中我有每个变量的频率和百分比，但我遇到了麻烦，因为在某些情况下有多个相同变量的列。

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

我相信我需要将这些变量转换为 long，然后使用 summarise/mutate 来获取频率，但我似乎无法弄清楚。非常感谢任何帮助。

Answer 1

您可以使用tidyverse 包将数据转换为长格式，然后汇总所需的统计信息。

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

Answer 2

合并和添加到：

1. Merge multiple frequency tables together in R

2. Adding a column of total n for each group in a stacked frequency table

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

Answer 3

在 base R

中尝试 list 中的 matrix

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

获取data.frame

data.frame( do.call( rbind, sapply( uniq, function(x){ 
  tbl <- table( unlist( dat[,grep( x, colnames(dat) )] ) ); 
  rbind( cbind( Percent=round( tbl/sum(tbl)*100, digits=2 ), Freq=tbl, var=x ), 
         cbind( sum(tbl/sum(tbl)*100), sum(tbl), var=x ) ) } )
 ) )
         Percent Freq   var
blue       27.27    3 color
green      18.18    2 color
red        18.18    2 color
yellow     36.36    4 color
X            100   11 color
circle        50    5 shape
square        20    2 shape
triangle      30    3 shape
X.1          100   10 shape
large      33.33    2  size
medium     33.33    2  size
small      33.33    2  size
X.2          100    6  size

数据

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))