我有这样的数据
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我试图根据两栏
对它们进行分类我可以做以下
df<- structure(list(V1 = structure(c(10L, 4L, 7L, 5L, 3L, 1L, 8L,
11L, 12L, 9L, 2L, 6L), .Label = c("BRA_AC_A6IX", "BRA_BH_A18F",
"BRA_BH_A18V", "BRA_BH_A1ES", "BRA_BH_A1FE", "BRA_BH_A6R8", "BRA_E2_A15A",
"BRA_E2_A15K", "BRA_E2_A1B4", "BRA_EM_A15E", "BRA_LQ_A4E4", "BRA_OK_A5Q2"
), class = "factor"), V2 = structure(c(2L, 3L, 5L, 3L, 3L, 5L,
3L, 4L, 1L, 4L, 2L, 2L), .Label = c("Level ii", "Level iia",
"Level iib", "Level iiia", "Level iiic"), class = "factor"),
V3 = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 4L), .Label = c("amira", "boro", "car", "dim"), class = "factor")), class = "data.frame", row.names = c(NA,
-12L))
但我希望有这样的输出
library(dplyr)
df %>%
+ group_by(V2) %>%
+ summarise(no_rows = length(V2))
# A tibble: 5 x 2
V2 no_rows
<fct> <int>
1 Level ii 1
2 Level iia 3
3 Level iib 4
4 Level iiia 2
5 Level iiic 2
答案 0 :(得分:0)
怎么样
library(reshape2)
df1 <- df[,-1]
table(melt(df1, id.var="V2")[-2])
答案 1 :(得分:0)
这是tidyverse
方法。我估计你真的想要计数,但如果你只想要容易添加的存在/缺席。
df <- structure(list(V1 = structure(c(10L, 4L, 7L, 5L, 3L, 1L, 8L, 11L, 12L, 9L, 2L, 6L), .Label = c("BRA_AC_A6IX", "BRA_BH_A18F", "BRA_BH_A18V", "BRA_BH_A1ES", "BRA_BH_A1FE", "BRA_BH_A6R8", "BRA_E2_A15A", "BRA_E2_A15K", "BRA_E2_A1B4", "BRA_EM_A15E", "BRA_LQ_A4E4", "BRA_OK_A5Q2"), class = "factor"), V2 = structure(c(2L, 3L, 5L, 3L, 3L, 5L, 3L, 4L, 1L, 4L, 2L, 2L), .Label = c("Level ii", "Level iia", "Level iib", "Level iiia", "Level iiic"), class = "factor"), V3 = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L), .Label = c("amira", "boro", "car", "dim"), class = "factor")), class = "data.frame", row.names = c(NA, -12L))
library(tidyverse)
df %>%
select(-V1) %>%
count(V2, V3) %>%
spread(V3, n, fill = 0L)
#> # A tibble: 5 x 5
#> V2 amira boro car dim
#> <fct> <int> <int> <int> <int>
#> 1 Level ii 0 0 1 0
#> 2 Level iia 1 0 1 1
#> 3 Level iib 1 2 1 0
#> 4 Level iiia 0 0 2 0
#> 5 Level iiic 1 1 0 0
由reprex package(v0.2.0)创建于2018-05-23。