How to drop observations based on conditions
1
I have a subset data that has a total count for each observation from a bigger dataset. If I want to drop duplicates based on a higher count and drop codes that appear less if the name is the same, how would I go about that? So for instance:
name = c("a", "a", "b", "b", "b", "c", "d", "e", "e", "e")
code = c(1,1,2,3,4,1,1,2,2,3)
n = c(1,10,2,3,5,4,8,100,90,40)
data = data.frame(name,code,n)
The end product would be left with these:
name = c("a", "b", "c", "d", "e")
code = c(1,4,1,1,2)
n = c(10,5,4,8,100)
data2 = data.frame(name,code,n)
r duplicates
asked Nov 14 '18 at 19:32
SunSun
596
add a comment |
1
I have a subset data that has a total count for each observation from a bigger dataset. If I want to drop duplicates based on a higher count and drop codes that appear less if the name is the same, how would I go about that? So for instance:
name = c("a", "a", "b", "b", "b", "c", "d", "e", "e", "e")
code = c(1,1,2,3,4,1,1,2,2,3)
n = c(1,10,2,3,5,4,8,100,90,40)
data = data.frame(name,code,n)
The end product would be left with these:
name = c("a", "b", "c", "d", "e")
code = c(1,4,1,1,2)
n = c(10,5,4,8,100)
data2 = data.frame(name,code,n)
r duplicates
asked Nov 14 '18 at 19:32
SunSun
596
1
Side note: do not dodata.frame(cbind(...)). You've turned all your numeric variables into characters. The functiondata.frame()is all you need:data.frame(name,code,n).
– joran
Nov 14 '18 at 19:34
1
@joran Thank you. will change that now
– Sun
Nov 14 '18 at 19:42
2
Possible duplicate of Remove duplicates keeping entry with largest absolute value
– Daniel Fischer
Nov 14 '18 at 19:56
add a comment |
1
1
1
I have a subset data that has a total count for each observation from a bigger dataset. If I want to drop duplicates based on a higher count and drop codes that appear less if the name is the same, how would I go about that? So for instance:
name = c("a", "a", "b", "b", "b", "c", "d", "e", "e", "e")
code = c(1,1,2,3,4,1,1,2,2,3)
n = c(1,10,2,3,5,4,8,100,90,40)
data = data.frame(name,code,n)
The end product would be left with these:
name = c("a", "b", "c", "d", "e")
code = c(1,4,1,1,2)
n = c(10,5,4,8,100)
data2 = data.frame(name,code,n)
r duplicates
asked Nov 14 '18 at 19:32
SunSun
596
I have a subset data that has a total count for each observation from a bigger dataset. If I want to drop duplicates based on a higher count and drop codes that appear less if the name is the same, how would I go about that? So for instance:
name = c("a", "a", "b", "b", "b", "c", "d", "e", "e", "e")
code = c(1,1,2,3,4,1,1,2,2,3)
n = c(1,10,2,3,5,4,8,100,90,40)
data = data.frame(name,code,n)
The end product would be left with these:
name = c("a", "b", "c", "d", "e")
code = c(1,4,1,1,2)
n = c(10,5,4,8,100)
data2 = data.frame(name,code,n)
r duplicates
r duplicates
asked Nov 14 '18 at 19:32
SunSun
596
asked Nov 14 '18 at 19:32
SunSun
596
edited Nov 14 '18 at 19:42
Sun
asked Nov 14 '18 at 19:32
SunSun
596
asked Nov 14 '18 at 19:32
SunSun
596
asked Nov 14 '18 at 19:32
SunSun
596
596
1
Side note: do not dodata.frame(cbind(...)). You've turned all your numeric variables into characters. The functiondata.frame()is all you need:data.frame(name,code,n).
– joran
Nov 14 '18 at 19:34
1
@joran Thank you. will change that now
– Sun
Nov 14 '18 at 19:42
2
Possible duplicate of Remove duplicates keeping entry with largest absolute value
– Daniel Fischer
Nov 14 '18 at 19:56
add a comment |
1
Side note: do not dodata.frame(cbind(...)). You've turned all your numeric variables into characters. The functiondata.frame()is all you need:data.frame(name,code,n).
– joran
Nov 14 '18 at 19:34
1
@joran Thank you. will change that now
– Sun
Nov 14 '18 at 19:42
2
Possible duplicate of Remove duplicates keeping entry with largest absolute value
– Daniel Fischer
Nov 14 '18 at 19:56
1
1
Side note: do not do
data.frame(cbind(...)). You've turned all your numeric variables into characters. The function data.frame() is all you need: data.frame(name,code,n).– joran
Nov 14 '18 at 19:34
Side note: do not do
data.frame(cbind(...)). You've turned all your numeric variables into characters. The function data.frame() is all you need: data.frame(name,code,n).– joran
Nov 14 '18 at 19:34
1
1
@joran Thank you. will change that now
– Sun
Nov 14 '18 at 19:42
@joran Thank you. will change that now
– Sun
Nov 14 '18 at 19:42
2
2
Possible duplicate of Remove duplicates keeping entry with largest absolute value
– Daniel Fischer
Nov 14 '18 at 19:56
Possible duplicate of Remove duplicates keeping entry with largest absolute value
– Daniel Fischer
Nov 14 '18 at 19:56
add a comment |
1 Answer
1
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oldest
votes
1
If you can use dplyr, this should do the trick:
library(dplyr)
data %>%
group_by(name) %>%
filter(n == max(n)) %>%
ungroup()
answered Nov 14 '18 at 21:35
dmcadmca
443414
add a comment |
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1 Answer
1
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1 Answer
1
active
oldest
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1
If you can use dplyr, this should do the trick:
library(dplyr)
data %>%
group_by(name) %>%
filter(n == max(n)) %>%
ungroup()
answered Nov 14 '18 at 21:35
dmcadmca
443414
add a comment |
1
If you can use dplyr, this should do the trick:
library(dplyr)
data %>%
group_by(name) %>%
filter(n == max(n)) %>%
ungroup()
answered Nov 14 '18 at 21:35
dmcadmca
443414
add a comment |
1
1
1
If you can use dplyr, this should do the trick:
library(dplyr)
data %>%
group_by(name) %>%
filter(n == max(n)) %>%
ungroup()
answered Nov 14 '18 at 21:35
dmcadmca
443414
If you can use dplyr, this should do the trick:
library(dplyr)
data %>%
group_by(name) %>%
filter(n == max(n)) %>%
ungroup()
answered Nov 14 '18 at 21:35
dmcadmca
443414
answered Nov 14 '18 at 21:35
dmcadmca
443414
answered Nov 14 '18 at 21:35
dmcadmca
443414
answered Nov 14 '18 at 21:35
dmcadmca
443414
443414
add a comment |
add a comment |
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1
Side note: do not do
data.frame(cbind(...)). You've turned all your numeric variables into characters. The functiondata.frame()is all you need:data.frame(name,code,n).– joran
Nov 14 '18 at 19:34
1
@joran Thank you. will change that now
– Sun
Nov 14 '18 at 19:42
2
Possible duplicate of Remove duplicates keeping entry with largest absolute value
– Daniel Fischer
Nov 14 '18 at 19:56