data.frame에서 가장 빈번한 요소 [중복]
Aug 20 2020
내 샘플 데이터를 아래에서 찾으십시오. '가장 빈번한'열에서 가장 빈번한 번호를 식별하고 싶습니다.
structure(list(name = c("act1_25", "act1_26", "act1_27", "act1_28",
"act1_29", "act1_30", "act1_31", "act1_32", "act1_33", "act1_34",
"act1_35", "act1_36", "act1_37", "act1_38", "act1_39", "act1_40",
"act1_41", "act1_42", "act1_43", "act1_44", "act1_45", "act1_46",
"act1_47", "act1_48", "serial"), `Most frequent` = c("111,110,9120,310,3110,210,1110",
"210,3110,110,310,9120,9210,8210,3819,1110,111", "210,110,310,8210,3110,1110",
"210,9120,110,310,8210,1110,3819", "210,9120,310,110,1110,111",
"9120,110,1110,3830", "110,1110,3210,310", "210,110,1110,8210,310",
"1110,310,8210,110", "210,310,1110,8210,110", "310,1110,8210,210,110",
"3210,9120,1110,8210,110", "1110,210,310,110,3830", "1110,210,310,110,3210,3830",
"1110,8210,110,3830,3210", "1110,310,110,3210,5190", "1110,110,5190",
"1110,3210,3830,310,8210,110,5190", "1110,8210,310,210,1120,110",
"1110,8210,310", "1110,8210,310", "1110,8210,310,110", "1110,8210,310,110",
"210,1110,8210,5190,110", "27080618")), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -25L))
Example of Output
Most frequent: 110
답변
2 Duck Aug 20 2020 at 20:30
나는 tidyverse접근 방식 을 제안합니다 .
library(tidyr)
library(dplyr)
#Separate rows
df %>% separate_rows(`Most frequent`,2,sep = ',') %>%
group_by(`Most frequent`) %>%
summarise(N=n()) %>% arrange(desc(N))
산출:
Most frequent N
1 1110 24
2 110 22
3 310 19
4 8210 16
5 210 12
6 3210 6
7 9120 6
8 3830 5
9 5190 4
10 111 3
11 3110 3
12 3819 2
13 1120 1
14 27080618 1
15 9210 1
@AllanCameron 결과와 유사합니다.
3 AllanCameron Aug 20 2020 at 20:27
넌 할 수있어
names(which.max(table(unlist(strsplit(df$`Most frequent`, ",")))))
#> [1] "1110"
또는 실제 개수와 함께 값을 원한다면 다음을 수행 할 수 있습니다.
rev(sort(table(unlist(strsplit(df$`Most frequent`, ",")))))[1]
#> 1110
#> 24
110 개의 항목이 22 개 항목 인 것과 비교하여 1110 개의 항목이 실제로 24 개 있음을 알 수 있습니다.
rev(sort(table(unlist(strsplit(df$`Most frequent`, ",")))))
#> 1110 110 310 8210 210 9120 3210 3830
#> 24 22 19 16 12 6 6 5
#> 5190 3110 111 3819 9210 27080618 1120
#> 4 3 3 2 1 1 1
1 iamericfletcher Aug 20 2020 at 20:43
df <- structure(list(name = c("act1_25", "act1_26", "act1_27", "act1_28",
"act1_29", "act1_30", "act1_31", "act1_32", "act1_33", "act1_34",
"act1_35", "act1_36", "act1_37", "act1_38", "act1_39", "act1_40",
"act1_41", "act1_42", "act1_43", "act1_44", "act1_45", "act1_46",
"act1_47", "act1_48", "serial"), `Most frequent` = c("111,110,9120,310,3110,210,1110",
"210,3110,110,310,9120,9210,8210,3819,1110,111", "210,110,310,8210,3110,1110",
"210,9120,110,310,8210,1110,3819", "210,9120,310,110,1110,111",
"9120,110,1110,3830", "110,1110,3210,310", "210,110,1110,8210,310",
"1110,310,8210,110", "210,310,1110,8210,110", "310,1110,8210,210,110",
"3210,9120,1110,8210,110", "1110,210,310,110,3830", "1110,210,310,110,3210,3830",
"1110,8210,110,3830,3210", "1110,310,110,3210,5190", "1110,110,5190",
"1110,3210,3830,310,8210,110,5190", "1110,8210,310,210,1120,110",
"1110,8210,310", "1110,8210,310", "1110,8210,310,110", "1110,8210,310,110",
"210,1110,8210,5190,110", "27080618")), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -25L))
library(dplyr)
library(tidyr)
df %>%
#//separate Most frequent using , as the separator
separate_rows(`Most frequent`, sep = ",") %>%
#//count the unique values of the Most Frequent variable with results in new column named frequency
count(`Most frequent`, name = "frequency") %>%
#//arrange frequency column in descending order
arrange(desc(frequency))
#> # A tibble: 15 x 2
#> `Most frequent` frequency
#> <chr> <int>
#> 1 1110 24
#> 2 110 22
#> 3 310 19
#> 4 8210 16
#> 5 210 12
#> 6 3210 6
#> 7 9120 6
#> 8 3830 5
#> 9 5190 4
#> 10 111 3
#> 11 3110 3
#> 12 3819 2
#> 13 1120 1
#> 14 27080618 1
#> 15 9210 1