R - 数据框的操作

Question

我有以下数据框table

S/N	Index 1	Index 2
A	5	5
B	5	2
C	2	4

如何改成下面的table？

index	1	2	3	4	5
Index 1	0%	33.3%	0%	0%	66.6%
Index 2	0%	33.3%	0%	33.3%	33.3%

提前致谢！

Answer 1

您似乎想查看每个值在每个索引中的计数分数。我花了一些步骤，但这是否大致产生了您要找的东西？

df1 <- data.frame("S_N" = c("A", "B", "C"),
                 "Index1" = c(5, 5, 2),
                 "Index2" = c(5, 2, 4))
df1 <- df1 %>% 
  pivot_longer(names_to = "Index", values_to = "value", cols = c("Index1", "Index2"))

df2 <- df1 %>% 
  group_by(Index) %>% 
  summarise(idx_cnt = n())

final_df <- df1 %>% 
  group_by(Index, value) %>% 
  summarise(count = n()) %>% 
  left_join(df2, by = "Index") %>% 
  mutate(frac = count / idx_cnt * 100) %>% 
  select(Index, value, frac) %>% 
  pivot_wider(names_from = value, values_from = frac)

结果：

> final_df
# A tibble: 2 x 4
# Groups:   Index [2]
  Index    `2`   `5`   `4`
  <chr>  <dbl> <dbl> <dbl>
1 Index1  33.3  66.7  NA  
2 Index2  33.3  33.3  33.3

Answer 2

这里使用tidyverse函数是一种方法。使用从@Carey Caginalp

共享的数据

library(tidyverse)

df1 %>%
  pivot_longer(cols = -S_N, names_to = 'index') %>%
  count(index, value) %>%
  group_by(index) %>%
  mutate(n = prop.table(n) * 100) %>%
  ungroup %>%
  complete(index, value = 1:max(value), fill = list(n = 0)) %>%
  pivot_wider(names_from = value, values_from = n)

#  index    `1`   `2`   `3`   `4`   `5`
#  <chr>  <dbl> <dbl> <dbl> <dbl> <dbl>
#1 Index1     0  33.3     0   0    66.7
#2 Index2     0  33.3     0  33.3  33.3

Answer 3

janitor

的简单语法

library(tidyverse)
library(janitor)

df1 %>% pivot_longer(-S_N) %>%
  tabyl(name, value) %>%
  adorn_percentages("row") %>%
  adorn_pct_formatting(digits = 2)

   name      2      4      5
 Index1 33.33%  0.00% 66.67%
 Index2 33.33% 33.33% 33.33%

R - 数据框的操作

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