My question has to do with order of plot bars when using ggplot.
EffectNames = c("Pull Back(A)","Hook(B)","Peg(C)","AB","BC","AC","ABC")
Half_Effect = c(10.4, 6.5, 5.6, 1.6, 0.98, .77, .65)
paretoData = cbind(EffectNames, Half_Effect)
paretoData = as.data.frame(paretoData)
ggplot(paretoData, aes(x = EffectNames, y = Half_Effect)) +
geom_bar(stat = "identity") +
geom_text(aes(label = Half_Effect), vjust = 1.5, colour = "white")
Result: Bar heights are in following order
1.6 0.65 0.77 0.98 6.5 5.6 10.4
AB ABC AC BC Hook(B) Peg(C) PullBack(A)
Bar heights are not in order seen in Half_Effect. How to force ordering of EffectNames to match descending order of Half_Effect? Can this be done in ggplot2? Yes it can! See solution below.
EffectNames=c( "Pull Back(A)","Hook(B)", "Peg(C)","AB", "BC", "AC", "ABC")
Half_Effect=c( 10.4,6.5,5.6,1.6,0.98,.77,.65 )
paretoData=data.frame(EffectNames, Half_Effect)
paretoData
paretoData$EffectNames = factor(paretoData$EffectNames,
levels=c("Pull Back(A)","Hook(B)", "Peg(C)","AB", "BC", "AC", "ABC"))
p=ggplot(paretoData, aes(x=EffectNames, y=Half_Effect)) +
geom_bar(stat="identity") +
geom_text(aes(label=Half_Effect), vjust=1.5, colour="white")
p
The independent variable belongs on the x-axis (horizontal line) of the graph and the dependent variable belongs on the y-axis (vertical line). The x and y axes cross at a point referred to as the origin, where the coordinates are (0,0).
To reorder the boxplot we will use reorder() function of ggplot2. By default, ggplot2 orders the groups in alphabetical order.
The reorder function is used here to change the order of the graphs. Here if you want ascending order then you'll use '+' plus sign, if you want in descending order then you should use '-' minus sign. Note: Column2 must be the column with numeric data.
Elaborating eipi10's comment, the reordering of levels can by accomplished conveniently using Hadley's forcats
package. In addition, the reordering can be done within the call to aes()
instead of manipulating the underlying data. This offers additional flexibilty in finding a suitable graphical display.
paretoData <- data.frame(
EffectNames = c("Pull Back(A)", "Hook(B)", "Peg(C)", "AB", "BC", "AC", "ABC"),
Half_Effect = c(10.4, 6.5, 5.6, 1.6, 0.98, .77, .65))
library(ggplot2)
p <- ggplot(paretoData, aes(x = EffectNames, y = Half_Effect)) +
geom_bar(stat = "identity") +
geom_text(aes(label = Half_Effect), vjust = 1.5, colour = "white")
p
Here, the order is alphabetical by default.
library(forcats)
p + aes(x = fct_inorder(EffectNames))
Half_Effect
, so no real surprise here.)fct_inorder()
saves us from typing the same stuff twice which would be required when explicitely specifying the levels in a call to factor
.p
was modified by only changing the x
aesthetics. The underlying data needn't to be touched.p + aes(x = fct_reorder(EffectNames, Half_Effect))
Here, the levels are ordered by increasing value of Half_Effect
. We could have achieved the same effect by using reorder()
from base R instead of fct_reorder()
.
To show the levels in decreasing order as requested by the OP we can do
p + aes(x = fct_reorder(EffectNames, Half_Effect, .desc = TRUE))
Note that reorder()
has no explicit parameter to reverse the order so we would need to modify the controlling variable reorder(EffectNames, -Half_Effect)
.
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