当组名出现在不同的行中时，如何聚合data.frame

Question

我有一个像这样的data.frame

df=data.frame(
grp=c("group1","s1","s2","s3","s4","s5","group2","s6","s7","s8","group2","s9","s10","group3","s11","s12","s13","s14"),
gname=c("gene1",0.00,0.05,0.01,0.01,0.01,"gene1",0.063,0.005,0.015,"gene2",0.07,0.00,"gene3",0.046,0.007,0.011,0.012),
score=c(0.989003844,NA,NA,NA,NA,NA,0.988334014,NA,NA,NA,0.983461712,NA,NA,0.982339339,NA,NA,NA,NA)
)

> df
      grp gname      score
1  group1 gene1 0.9890038
2      s1     0        NA
3      s2  0.05        NA
4      s3  0.01        NA
5      s4  0.01        NA
6      s5  0.01        NA
7  group2 gene1 0.9883340
8      s6 0.063        NA
9      s7 0.005        NA
10     s8 0.015        NA
11 group2 gene2 0.9834617
12     s9  0.07        NA
13    s10     0        NA
14 group3 gene3 0.9823393
15    s11 0.046        NA
16    s12 0.007        NA
17    s13 0.011        NA
18    s14 0.012        NA

根据组和基因名称，将df分为4个部分。下图显示了这4个部分。

我将根据各列{{1}汇总每个部分的df，以找到max的{​​{1}}和df$score的{​​{1}} }和length。以下df显示了预期结果。

df$grp

以及下图显示了如何获得结果。

如何为每个部分执行df$grp和df$gname并将结果保存在data.frame中。

Answer 1

如果您知道每个组均以不遗漏的分数开头，然后是遗漏的值，则可以结合使用cumsum/is.na和tapply。

首先创建一个聚合变量f。

f <- cumsum(!is.na(df$score))

现在看看结果长度是多少。数字的最上面一行是"names"属性的值，长度是最下面一行。这些长度包括"group*"行，因此在最终数据帧中减去1。

tapply(f, f, length)
#1 2 3 4 
#6 4 3 5 

创建问题要求的结果。

result <- cbind(df[!is.na(df$score), ], length = tapply(f, f, length) - 1)

result
#      grp gname     score length
#1  group1 gene1 0.9890038      5
#7  group2 gene1 0.9883340      3
#11 group2 gene2 0.9834617      2
#14 group3 gene3 0.9823393      4

如果您进一步想要连续的行名，

row.names(result) <- NULL

Answer 2

带有tidyverse

的选项

library(dplyr)
df %>% 
  group_by(grp1 = cumsum(grepl("group", grp))) %>%
  mutate(length = n() -1) %>%
  slice(1) %>%
  ungroup %>%
  select(-grp1)
# A tibble: 4 x 4
#  grp    gname score length
#  <fct>  <fct> <dbl>  <dbl>
#1 group1 gene1 0.989      5
#2 group2 gene1 0.988      3
#3 group2 gene2 0.983      2
#4 group3 gene3 0.982      4