[英]Subset data.frame by column
I have this data.frame: 我有这个data.frame:
a <- c(rep("1", 3), rep("2", 3), rep("3",3), rep("4",3), rep("5",3))
b <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
df <-data.frame(a,b)
a b
1 1 1
2 1 2
3 1 3
4 2 4
5 2 5
6 2 6
7 3 7
8 3 8
9 3 9
10 4 10
11 4 11
12 4 12
13 5 13
14 5 14
15 5 15
I want to have something like this: 我想要这样的东西:
a <- c(rep("2", 3), rep("3", 3))
b <- c(4,5,6,7,8,9)
dffinal<-data.frame(a,b)
a b
1 2 4
2 2 5
3 2 6
4 3 7
5 3 8
6 3 9
I could use the "subset" function, but its not working 我可以使用“子集”功能,但无法正常工作
sub <- subset(df,c(2,3) == a )
a b
5 2 5
8 3 8
This command only takes one row of "2" and "3" in column "a". 该命令仅在列“ a”中使用一行“ 2”和“ 3”。
Any Help? 有帮助吗?
what about this? 那这个呢?
library(dplyr)
df %>% filter(a == 2 | a==3)
a b
1 2 4
2 2 5
3 2 6
4 3 7
5 3 8
6 3 9
You're confusing ==
with %in%
: 您将
==
与%in%
混淆了:
subset(df, a %in% c(2,3))
# a b
# 4 2 4
# 5 2 5
# 6 2 6
# 7 3 7
# 8 3 8
# 9 3 9
We can use data.table
. 我们可以使用
data.table
。 We convert the 'data.frame' to 'data.table' ( setDT(df)
), and set the 'key' as column 'a', then we subset the rows. 我们将'data.frame'转换为'data.table'(
setDT(df)
),并将'key'设置为'a'列,然后对行进行子集化。
library(data.table)
setDT(df, key= 'a')[c('2','3')]
# a b
#1: 2 4
#2: 2 5
#3: 2 6
#4: 3 7
#5: 3 8
#6: 3 9
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