How to find a column value based on the unique value for another column
1
I have the following dataset:
Class Value
A 5.4
A 5.4
A 5.4
B 3.6
B 2.7
C 4.02
C 4.02
C 4.02
D 6.33
D 6.33
What I want is to retrieve only the classes that have similar values, which in this case should return the class A and D but not, for example, the class B since it has two different values.
To do that, I tried the following:
sub <- dataset[as.logical(ave(dataset$Value, dataset$Class, FUN = function(x) all(x==x))), ]
But this returns all the classes which I don't want.
Can someone help me with that?
r
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
add a comment |
1
I have the following dataset:
Class Value
A 5.4
A 5.4
A 5.4
B 3.6
B 2.7
C 4.02
C 4.02
C 4.02
D 6.33
D 6.33
What I want is to retrieve only the classes that have similar values, which in this case should return the class A and D but not, for example, the class B since it has two different values.
To do that, I tried the following:
sub <- dataset[as.logical(ave(dataset$Value, dataset$Class, FUN = function(x) all(x==x))), ]
But this returns all the classes which I don't want.
Can someone help me with that?
r
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
add a comment |
1
1
1
I have the following dataset:
Class Value
A 5.4
A 5.4
A 5.4
B 3.6
B 2.7
C 4.02
C 4.02
C 4.02
D 6.33
D 6.33
What I want is to retrieve only the classes that have similar values, which in this case should return the class A and D but not, for example, the class B since it has two different values.
To do that, I tried the following:
sub <- dataset[as.logical(ave(dataset$Value, dataset$Class, FUN = function(x) all(x==x))), ]
But this returns all the classes which I don't want.
Can someone help me with that?
r
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
I have the following dataset:
Class Value
A 5.4
A 5.4
A 5.4
B 3.6
B 2.7
C 4.02
C 4.02
C 4.02
D 6.33
D 6.33
What I want is to retrieve only the classes that have similar values, which in this case should return the class A and D but not, for example, the class B since it has two different values.
To do that, I tried the following:
sub <- dataset[as.logical(ave(dataset$Value, dataset$Class, FUN = function(x) all(x==x))), ]
But this returns all the classes which I don't want.
Can someone help me with that?
r
r
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
asked Jan 18 at 20:09
Adam AminAdam Amin
31018
31018
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
3
Using aggregate with number of unique (length(unique))
filterdf=aggregate(Value ~ Class, df, function(x) length(unique(x)))
df[df$Class%in%filterdf[filterdf$Value==1,]$Class,]
Class Value
1 A 5.40
2 A 5.40
3 A 5.40
6 C 4.02
7 C 4.02
8 C 4.02
9 D 6.33
10 D 6.33
Alternative from markus
idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1)
df[idx, ]
answered Jan 18 at 20:17
W-BW-B
107k83165
3
I was about to post a similar solution usingavewhich you might want to add as alternative.idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]
– markus
Jan 18 at 20:22
1
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
2
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
add a comment |
0
With tidyverse you can do:
df %>%
group_by(Class) %>%
filter(all(Value == first(Value)))
Or:
df %>%
group_by(Class) %>%
filter(n_distinct(Value) == 1)
Or:
df %>%
group_by(Class) %>%
filter(all(Value %/% first(Value) != 0))
Or:
df %>%
group_by(Class, Value) %>%
mutate(temp = seq_along(Value)) %>%
group_by(Class) %>%
filter(sum(temp[temp == 1]) == 1) %>%
select(-temp)
Or basically the same as the post from @W-B:
df %>%
group_by(Class) %>%
filter(length(unique(Value)) == 1)
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
3
Using aggregate with number of unique (length(unique))
filterdf=aggregate(Value ~ Class, df, function(x) length(unique(x)))
df[df$Class%in%filterdf[filterdf$Value==1,]$Class,]
Class Value
1 A 5.40
2 A 5.40
3 A 5.40
6 C 4.02
7 C 4.02
8 C 4.02
9 D 6.33
10 D 6.33
Alternative from markus
idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1)
df[idx, ]
answered Jan 18 at 20:17
W-BW-B
107k83165
3
I was about to post a similar solution usingavewhich you might want to add as alternative.idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]
– markus
Jan 18 at 20:22
1
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
2
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
add a comment |
3
Using aggregate with number of unique (length(unique))
filterdf=aggregate(Value ~ Class, df, function(x) length(unique(x)))
df[df$Class%in%filterdf[filterdf$Value==1,]$Class,]
Class Value
1 A 5.40
2 A 5.40
3 A 5.40
6 C 4.02
7 C 4.02
8 C 4.02
9 D 6.33
10 D 6.33
Alternative from markus
idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1)
df[idx, ]
answered Jan 18 at 20:17
W-BW-B
107k83165
3
I was about to post a similar solution usingavewhich you might want to add as alternative.idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]
– markus
Jan 18 at 20:22
1
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
2
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
add a comment |
3
3
3
Using aggregate with number of unique (length(unique))
filterdf=aggregate(Value ~ Class, df, function(x) length(unique(x)))
df[df$Class%in%filterdf[filterdf$Value==1,]$Class,]
Class Value
1 A 5.40
2 A 5.40
3 A 5.40
6 C 4.02
7 C 4.02
8 C 4.02
9 D 6.33
10 D 6.33
Alternative from markus
idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1)
df[idx, ]
answered Jan 18 at 20:17
W-BW-B
107k83165
Using aggregate with number of unique (length(unique))
filterdf=aggregate(Value ~ Class, df, function(x) length(unique(x)))
df[df$Class%in%filterdf[filterdf$Value==1,]$Class,]
Class Value
1 A 5.40
2 A 5.40
3 A 5.40
6 C 4.02
7 C 4.02
8 C 4.02
9 D 6.33
10 D 6.33
Alternative from markus
idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1)
df[idx, ]
answered Jan 18 at 20:17
W-BW-B
107k83165
edited Jan 18 at 20:29
answered Jan 18 at 20:17
W-BW-B
107k83165
answered Jan 18 at 20:17
W-BW-B
107k83165
answered Jan 18 at 20:17
W-BW-B
107k83165
107k83165
3
I was about to post a similar solution usingavewhich you might want to add as alternative.idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]
– markus
Jan 18 at 20:22
1
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
2
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
add a comment |
3
I was about to post a similar solution usingavewhich you might want to add as alternative.idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]
– markus
Jan 18 at 20:22
1
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
2
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
3
3
I was about to post a similar solution using
ave which you might want to add as alternative. idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]– markus
Jan 18 at 20:22
I was about to post a similar solution using
ave which you might want to add as alternative. idx <- with(df, ave(Value, Class, FUN = function(x) length(unique(x))) == 1); df[idx, ]– markus
Jan 18 at 20:22
1
1
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
@markus that is great thank you :-) , if you would like convert it as an answer I will definitively upvote for you man
– W-B
Jan 18 at 20:24
2
2
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
That is kind of you. I found it too similiar to what you posted 1 minute earlier. Feel free to use it.
– markus
Jan 18 at 20:27
add a comment |
0
With tidyverse you can do:
df %>%
group_by(Class) %>%
filter(all(Value == first(Value)))
Or:
df %>%
group_by(Class) %>%
filter(n_distinct(Value) == 1)
Or:
df %>%
group_by(Class) %>%
filter(all(Value %/% first(Value) != 0))
Or:
df %>%
group_by(Class, Value) %>%
mutate(temp = seq_along(Value)) %>%
group_by(Class) %>%
filter(sum(temp[temp == 1]) == 1) %>%
select(-temp)
Or basically the same as the post from @W-B:
df %>%
group_by(Class) %>%
filter(length(unique(Value)) == 1)
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
add a comment |
0
With tidyverse you can do:
df %>%
group_by(Class) %>%
filter(all(Value == first(Value)))
Or:
df %>%
group_by(Class) %>%
filter(n_distinct(Value) == 1)
Or:
df %>%
group_by(Class) %>%
filter(all(Value %/% first(Value) != 0))
Or:
df %>%
group_by(Class, Value) %>%
mutate(temp = seq_along(Value)) %>%
group_by(Class) %>%
filter(sum(temp[temp == 1]) == 1) %>%
select(-temp)
Or basically the same as the post from @W-B:
df %>%
group_by(Class) %>%
filter(length(unique(Value)) == 1)
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
add a comment |
0
0
0
With tidyverse you can do:
df %>%
group_by(Class) %>%
filter(all(Value == first(Value)))
Or:
df %>%
group_by(Class) %>%
filter(n_distinct(Value) == 1)
Or:
df %>%
group_by(Class) %>%
filter(all(Value %/% first(Value) != 0))
Or:
df %>%
group_by(Class, Value) %>%
mutate(temp = seq_along(Value)) %>%
group_by(Class) %>%
filter(sum(temp[temp == 1]) == 1) %>%
select(-temp)
Or basically the same as the post from @W-B:
df %>%
group_by(Class) %>%
filter(length(unique(Value)) == 1)
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
With tidyverse you can do:
df %>%
group_by(Class) %>%
filter(all(Value == first(Value)))
Or:
df %>%
group_by(Class) %>%
filter(n_distinct(Value) == 1)
Or:
df %>%
group_by(Class) %>%
filter(all(Value %/% first(Value) != 0))
Or:
df %>%
group_by(Class, Value) %>%
mutate(temp = seq_along(Value)) %>%
group_by(Class) %>%
filter(sum(temp[temp == 1]) == 1) %>%
select(-temp)
Or basically the same as the post from @W-B:
df %>%
group_by(Class) %>%
filter(length(unique(Value)) == 1)
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
edited Jan 18 at 21:25
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
answered Jan 18 at 21:00
tmfmnktmfmnk
2,2941412
2,2941412
add a comment |
add a comment |
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