Adjust geom_histogram labels on bars VS correct scale on y-axis
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0
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I have this plot
ggplot(data, aes(D3)) +
geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) +
geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) +
scale_fill_gradient("", low = "green", high = "red")
which outputs a this nice histogram
as you can see y axis shows count instead of percentage.
On other hand if I switch to
ggplot(data, aes(D3)) +
geom_histogram(aes(y = (..density..)), binwidth = 1) +
geom_text(aes( label = format(100*..density.., digits=1,), y= ..density.. ), stat= "bin", binwidth =1, vjust = -0.2 ) +
scale_y_continuous(labels = scales::percent)
it outputs this (quite ugly) plot with zeroes on the y axis
How can I adjust y-axis on first plot, ie show percentage instead count? or remove those zeroes in the second?
r ggplot2
asked Nov 21 at 12:41
rmorelli74
364
add a comment |
up vote
0
down vote
favorite
I have this plot
ggplot(data, aes(D3)) +
geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) +
geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) +
scale_fill_gradient("", low = "green", high = "red")
which outputs a this nice histogram
as you can see y axis shows count instead of percentage.
On other hand if I switch to
ggplot(data, aes(D3)) +
geom_histogram(aes(y = (..density..)), binwidth = 1) +
geom_text(aes( label = format(100*..density.., digits=1,), y= ..density.. ), stat= "bin", binwidth =1, vjust = -0.2 ) +
scale_y_continuous(labels = scales::percent)
it outputs this (quite ugly) plot with zeroes on the y axis
How can I adjust y-axis on first plot, ie show percentage instead count? or remove those zeroes in the second?
r ggplot2
asked Nov 21 at 12:41
rmorelli74
364
1
This is easy enough to help with, using somedplyror other functions, if you make a reproducible example
– camille
Nov 21 at 13:19
@camille well, I know how to deal with this usingdplyrand calculating percentage before going through ggplot but I am working with young students (17yr) and would like to keep it simple as possible using..count..without usingdplyr.
– rmorelli74
Nov 21 at 13:45
It's a little hard to tell without an example dataset, but my guess is you wanty = stat(count/sum(count))insideaes()in bothgeom_histogram()andgeom_text(). Then you can addscale_y_continuous(labels = scales::percent). (Thestat()code was introduced as the replacement for the..names starting in ggplot2 version 3.0.0.)
– aosmith
Nov 21 at 19:48
@aosmithdt <- as.data.frame(rnorm(500, 2000))colnames(dt) <- "D3"dt$D3 <- as.integer(dt$D3)ggplot(dt, aes(D3)) + geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) + geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) + scale_fill_gradient("", low = "green", high = "red")
– rmorelli74
Nov 22 at 7:26
You can go ahead and edit your question to add your dataset (don't forget to set your seed so it is reproducible!). Did you try what I suggested? I'm pretty sure it does what you want now that I see your example dataset.
– aosmith
2 days ago
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have this plot
ggplot(data, aes(D3)) +
geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) +
geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) +
scale_fill_gradient("", low = "green", high = "red")
which outputs a this nice histogram
as you can see y axis shows count instead of percentage.
On other hand if I switch to
ggplot(data, aes(D3)) +
geom_histogram(aes(y = (..density..)), binwidth = 1) +
geom_text(aes( label = format(100*..density.., digits=1,), y= ..density.. ), stat= "bin", binwidth =1, vjust = -0.2 ) +
scale_y_continuous(labels = scales::percent)
it outputs this (quite ugly) plot with zeroes on the y axis
How can I adjust y-axis on first plot, ie show percentage instead count? or remove those zeroes in the second?
r ggplot2
asked Nov 21 at 12:41
rmorelli74
364
I have this plot
ggplot(data, aes(D3)) +
geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) +
geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) +
scale_fill_gradient("", low = "green", high = "red")
which outputs a this nice histogram
as you can see y axis shows count instead of percentage.
On other hand if I switch to
ggplot(data, aes(D3)) +
geom_histogram(aes(y = (..density..)), binwidth = 1) +
geom_text(aes( label = format(100*..density.., digits=1,), y= ..density.. ), stat= "bin", binwidth =1, vjust = -0.2 ) +
scale_y_continuous(labels = scales::percent)
it outputs this (quite ugly) plot with zeroes on the y axis
How can I adjust y-axis on first plot, ie show percentage instead count? or remove those zeroes in the second?
r ggplot2
r ggplot2
asked Nov 21 at 12:41
rmorelli74
364
asked Nov 21 at 12:41
rmorelli74
364
edited Nov 21 at 12:52
asked Nov 21 at 12:41
rmorelli74
364
asked Nov 21 at 12:41
rmorelli74
364
asked Nov 21 at 12:41
rmorelli74
364
364
1
This is easy enough to help with, using somedplyror other functions, if you make a reproducible example
– camille
Nov 21 at 13:19
@camille well, I know how to deal with this usingdplyrand calculating percentage before going through ggplot but I am working with young students (17yr) and would like to keep it simple as possible using..count..without usingdplyr.
– rmorelli74
Nov 21 at 13:45
It's a little hard to tell without an example dataset, but my guess is you wanty = stat(count/sum(count))insideaes()in bothgeom_histogram()andgeom_text(). Then you can addscale_y_continuous(labels = scales::percent). (Thestat()code was introduced as the replacement for the..names starting in ggplot2 version 3.0.0.)
– aosmith
Nov 21 at 19:48
@aosmithdt <- as.data.frame(rnorm(500, 2000))colnames(dt) <- "D3"dt$D3 <- as.integer(dt$D3)ggplot(dt, aes(D3)) + geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) + geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) + scale_fill_gradient("", low = "green", high = "red")
– rmorelli74
Nov 22 at 7:26
You can go ahead and edit your question to add your dataset (don't forget to set your seed so it is reproducible!). Did you try what I suggested? I'm pretty sure it does what you want now that I see your example dataset.
– aosmith
2 days ago
add a comment |
1
This is easy enough to help with, using somedplyror other functions, if you make a reproducible example
– camille
Nov 21 at 13:19
@camille well, I know how to deal with this usingdplyrand calculating percentage before going through ggplot but I am working with young students (17yr) and would like to keep it simple as possible using..count..without usingdplyr.
– rmorelli74
Nov 21 at 13:45
It's a little hard to tell without an example dataset, but my guess is you wanty = stat(count/sum(count))insideaes()in bothgeom_histogram()andgeom_text(). Then you can addscale_y_continuous(labels = scales::percent). (Thestat()code was introduced as the replacement for the..names starting in ggplot2 version 3.0.0.)
– aosmith
Nov 21 at 19:48
@aosmithdt <- as.data.frame(rnorm(500, 2000))colnames(dt) <- "D3"dt$D3 <- as.integer(dt$D3)ggplot(dt, aes(D3)) + geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) + geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) + scale_fill_gradient("", low = "green", high = "red")
– rmorelli74
Nov 22 at 7:26
You can go ahead and edit your question to add your dataset (don't forget to set your seed so it is reproducible!). Did you try what I suggested? I'm pretty sure it does what you want now that I see your example dataset.
– aosmith
2 days ago
1
1
This is easy enough to help with, using some
dplyr or other functions, if you make a reproducible example– camille
Nov 21 at 13:19
This is easy enough to help with, using some
dplyr or other functions, if you make a reproducible example– camille
Nov 21 at 13:19
@camille well, I know how to deal with this using
dplyr and calculating percentage before going through ggplot but I am working with young students (17yr) and would like to keep it simple as possible using ..count.. without using dplyr.– rmorelli74
Nov 21 at 13:45
@camille well, I know how to deal with this using
dplyr and calculating percentage before going through ggplot but I am working with young students (17yr) and would like to keep it simple as possible using ..count.. without using dplyr.– rmorelli74
Nov 21 at 13:45
It's a little hard to tell without an example dataset, but my guess is you want
y = stat(count/sum(count)) inside aes() in both geom_histogram() and geom_text(). Then you can add scale_y_continuous(labels = scales::percent). (The stat() code was introduced as the replacement for the .. names starting in ggplot2 version 3.0.0.)– aosmith
Nov 21 at 19:48
It's a little hard to tell without an example dataset, but my guess is you want
y = stat(count/sum(count)) inside aes() in both geom_histogram() and geom_text(). Then you can add scale_y_continuous(labels = scales::percent). (The stat() code was introduced as the replacement for the .. names starting in ggplot2 version 3.0.0.)– aosmith
Nov 21 at 19:48
@aosmith
dt <- as.data.frame(rnorm(500, 2000)) colnames(dt) <- "D3" dt$D3 <- as.integer(dt$D3) ggplot(dt, aes(D3)) + geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) + geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) + scale_fill_gradient("", low = "green", high = "red")– rmorelli74
Nov 22 at 7:26
@aosmith
dt <- as.data.frame(rnorm(500, 2000)) colnames(dt) <- "D3" dt$D3 <- as.integer(dt$D3) ggplot(dt, aes(D3)) + geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) + geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) + scale_fill_gradient("", low = "green", high = "red")– rmorelli74
Nov 22 at 7:26
You can go ahead and edit your question to add your dataset (don't forget to set your seed so it is reproducible!). Did you try what I suggested? I'm pretty sure it does what you want now that I see your example dataset.
– aosmith
2 days ago
You can go ahead and edit your question to add your dataset (don't forget to set your seed so it is reproducible!). Did you try what I suggested? I'm pretty sure it does what you want now that I see your example dataset.
– aosmith
2 days ago
add a comment |
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1
This is easy enough to help with, using some
dplyror other functions, if you make a reproducible example– camille
Nov 21 at 13:19
@camille well, I know how to deal with this using
dplyrand calculating percentage before going through ggplot but I am working with young students (17yr) and would like to keep it simple as possible using..count..without usingdplyr.– rmorelli74
Nov 21 at 13:45
It's a little hard to tell without an example dataset, but my guess is you want
y = stat(count/sum(count))insideaes()in bothgeom_histogram()andgeom_text(). Then you can addscale_y_continuous(labels = scales::percent). (Thestat()code was introduced as the replacement for the..names starting in ggplot2 version 3.0.0.)– aosmith
Nov 21 at 19:48
@aosmith
dt <- as.data.frame(rnorm(500, 2000))colnames(dt) <- "D3"dt$D3 <- as.integer(dt$D3)ggplot(dt, aes(D3)) + geom_histogram(aes(fill=(..count..)/sum(..count..)), stat = "count", na.rm = TRUE, binwidth =1) + geom_text(aes(y = ((..count..)), label = scales::percent( (..count..)/sum(..count..)) ), stat = "count", vjust = -0.25) + scale_fill_gradient("", low = "green", high = "red")– rmorelli74
Nov 22 at 7:26
You can go ahead and edit your question to add your dataset (don't forget to set your seed so it is reproducible!). Did you try what I suggested? I'm pretty sure it does what you want now that I see your example dataset.
– aosmith
2 days ago