I am trying to create a plot in R using ggplot that shows the difference between my two bars in a nice way.
I found an example that did part of what I wanted, but I have two major problems:
It is based on comparing groups of bars, but I only have two, so I added one group with both of them.
I would like to draw the arrow in nicer shape. I attached an image.
Code:
transactions <- c(5000000, 1000000)
time <- c("Q1","Q2")
group <- c("A", "A")
data <- data.frame(transactions, time, group)
library(ggplot2)
fun.data <- function(x){
print(x)
return(data.frame(y = max(x) + 1,
label = paste0(round(diff(x), 2), "cm")))
}
ylab <- c(2.5, 5.0, 7.5, 10)
gg <- ggplot(data, aes(x = time, y = transactions, fill = colors_hc[1], label = round(transactions, 0))) +
geom_bar(stat = "identity", show.legend = FALSE) +
geom_text(position = position_dodge(width = 0.9),
vjust = 1.1) +
geom_line(aes(group = group), position = position_nudge(0.1),
arrow = arrow()) +
stat_summary(aes(x = group, y = transactions),
geom = "label",
fun.data = fun.data,
fontface = "bold", fill = "lightgrey",
inherit.aes = FALSE) +
expand_limits(x = c(0, NA), y = c(0, NA)) +
scale_y_continuous(labels = paste0(ylab, "M"),
breaks = 10 ^ 6 * ylab)
gg
The arrows I am aiming for:
Where I am (ignore the ugliness, didn't style it yet):
This works, but you still need to play around a bit with the axes (or rather beautify them)
library(dplyr)
library(ggplot2)
transactions <- c(5000000, 1000000)
time <- c("Q1","Q2")
group <- c("A", "A")
my_data <- data.frame(transactions, time, group)
fun.data <- function(x){
return(data.frame(y = max(x) + 1,
label = as.integer(diff(x))))
}
my_data %>%
ggplot(aes(x = group, y = transactions, fill = time)) +
geom_bar(stat = 'identity', position = 'dodge') +
geom_text(aes(label = as.integer(transactions)),
position = position_dodge(width = 0.9),
vjust = 1.5) +
geom_line(aes(group = group), position = position_nudge(0.1),
arrow = arrow()) +
stat_summary(aes(x = group, y = transactions),
geom = "label",
size = 5,
position = position_nudge(0.05),
fun.data = fun.data,
fontface = "bold", fill = "lightgrey",
inherit.aes = FALSE)
Edit2:
y_limit <- 6000000
my_data %>%
ggplot(aes(x = time, y = transactions)) +
geom_bar(stat = 'identity',
fill = 'steelblue') +
geom_text(aes(label = as.integer(transactions)),
vjust = 2) +
coord_cartesian(ylim = c(0, y_limit)) +
geom_segment(aes(x = 'Q1', y = max(my_data$transactions),
xend = 'Q1', yend = y_limit)) +
geom_segment(aes(x = 'Q2', y = y_limit,
xend = 'Q2', yend = min(my_data$transactions)),
arrow = arrow()) +
geom_segment(aes(x = 'Q1', y = y_limit,
xend = 'Q2', yend = y_limit)) +
geom_label(aes(x = 'Q2',
y = y_limit,
label = as.integer(min(my_data$transactions)- max(my_data$transactions))),
size = 10,
position = position_nudge(-0.5),
fontface = "bold", fill = "lightgrey")
Related
I have a ggplot with two y-axes by the sec.axis command, and I've been struggling with handling legends in these situations.
The code:
library(ggplot2)
library(ggrepel)
df <- data.frame(day = as.character(seq(from = 1, to = 100, by = 1)),
total = rbinom(n=100,30,0.5),
prop = runif(100))
df <- df %>% arrange(df, by = day)
df$`percentage` <- label_percent(accuracy = 0.01)(df$prop)
ggplot(data = df,
aes(x = day, y = total)) +
geom_bar(aes(x = day, y = total), stat = "identity", fill = "lightgreen", width = 0.35) +
geom_line(data = df,
aes(x = day, y = (prop)*15, group = 1, color = prop),
color = "red", size = 1,inherit.aes = TRUE) +
scale_y_continuous(
labels = function(x) format(x, scientific = FALSE),
#breaks = seq(from = 0, to = 10000000,by = 100000),
sec.axis = sec_axis(trans = ~./15,
name = "Secondary axis",
breaks = seq(from = 0, to = 10, by = 0.1),
scales::percent))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5))+
geom_label_repel(data=df[nrow(df),],
aes(x = day,
y = prop*15,
label = round(prop*100,2)),
color = 'red',
nudge_x = 2,
segment.alpha = 0.5) +
scale_x_discrete(expand = expansion(add = c(0, 7)))
And I wanted to simply have the legend, instead of having the axis description, like this:
I know it seems reasonably easy to obtain, but given the fact that I don’t have any groups, I either: can't plot any legend what so ever; or I get plotted two squares (when I wanted the legend to consist of a line, with the geom_line color and a square with the geom_bar color).
With the code #divibisan provided, I get the following output:
Final update:
I finally found the solution. I still have no idea how I got a different output from what #divibisan posted, but here goes what worked for me:
library(dplyr)
library(ggplot2)
library(ggrepel)
df <- data.frame(day = as.character(seq(from = 1, to = 100, by = 1)),
total = rbinom(n=100,30,0.5),
prop = runif(100))
df <- df %>% arrange(df, by = day)
df$`percentage` <- scales::label_percent(accuracy = 0.01)(df$prop)
ggplot(data = df,
aes(x = day, y = total)) +
geom_bar(aes(x = day, y = total, fill = "Total"), stat = "identity", width = 0.35) +
geom_line(data = df,
aes(x = day, y = (prop)*15, group = 1, color = 'Percentage'), size = 1,inherit.aes = TRUE) +
scale_y_continuous(
labels = function(x) format(x, scientific = FALSE),
#breaks = seq(from = 0, to = 10000000,by = 100000),
sec.axis = sec_axis(trans = ~./15,
name = "Secondary axis",
breaks = seq(from = 0, to = 10, by = 0.1),
scales::percent))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5))+
geom_label_repel(data=df[nrow(df),],
aes(x = day,
y = prop*15,
label = round(prop*100,2)),
color = 'red',
nudge_x = 2,
segment.alpha = 0.5) +
scale_x_discrete(expand = expansion(add = c(0, 7))) +
scale_fill_manual(values=c('Total' = 'lightgreen'), drop=TRUE, name='') +
scale_color_manual(values=c('Percentage' = "red"), drop=TRUE, name='') +
theme(legend.title = element_blank())
You just need to set the color/fill with a value in the aes, then use a scale function to set the color and create a legend. Here, we move the color= and fill= values from the bar and line into the aes. Then we add scale_fill/color_manual functions that set the color based on those names:
library(dplyr)
library(ggplot2)
library(ggrepel)
df <- data.frame(day = as.character(seq(from = 1, to = 100, by = 1)),
total = rbinom(n=100,30,0.5),
prop = runif(100))
df <- df %>% arrange(df, by = day)
df$`percentage` <- scales::label_percent(accuracy = 0.01)(df$prop)
ggplot(data = df,
aes(x = day, y = total)) +
geom_bar(aes(x = day, y = total, fill = "Total"), stat = "identity", width = 0.35) +
geom_line(data = df,
aes(x = day, y = (prop)*15, group = 1, color = 'Percentage'), size = 1,inherit.aes = TRUE) +
scale_y_continuous(
labels = function(x) format(x, scientific = FALSE),
#breaks = seq(from = 0, to = 10000000,by = 100000),
sec.axis = sec_axis(trans = ~./15,
name = "Secondary axis",
breaks = seq(from = 0, to = 10, by = 0.1),
scales::percent))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5))+
geom_label_repel(data=df[nrow(df),],
aes(x = day,
y = prop*15,
label = round(prop*100,2)),
color = 'red',
nudge_x = 2,
segment.alpha = 0.5) +
scale_x_discrete(expand = expansion(add = c(0, 7))) +
scale_fill_manual(values=c('Total' = 'lightgreen', 'Percentage'='red'), drop=TRUE, name='') +
scale_color_manual(values=c('Total' = 'lightgreen', 'Percentage'='red'), drop=TRUE, name='')
If, for some reason, the drop argument isn't working and both colors show up in both scales, there's really no reason to include them in the scale if they're not expected to be there. Just only include the colors in the scale that are desired:
scale_fill_manual(values=c('Total' = 'lightgreen'), drop=TRUE, name='') +
scale_color_manual(values=c('Percentage'='red'), drop=TRUE, name='')
I have code that plots paired points and also graphs half violin and box plots of pretest and posttest scores. I added lines between the paired points, but I am having difficulty with adding an arrow to the lines and changing the color depending on whether the score decreased or increased.
Below is my code and an image of my graph.
f5 <- ggplot(data = d, aes(y = y)) +
#Add geom_() objects
geom_point(data = d %>% filter(x =="1"), aes(x = xj), color = 'dodgerblue', size = 1.5,
alpha = .6) +
geom_point(data = d %>% filter(x =="2"), aes(x = xj), color = 'darkorange', size = 1.5,
alpha = .6) +
geom_line(aes(x = xj, group = id), color = 'lightgray', alpha = .3) +
geom_half_boxplot(
data = d %>% filter(x=="1"), aes(x=x, y = y), position = position_nudge(x = -.25),
side = "r",outlier.shape = NA, center = TRUE, errorbar.draw = FALSE, width = .2,
fill = 'dodgerblue') +
geom_half_boxplot(
data = d %>% filter(x=="2"), aes(x=x, y = y), position = position_nudge(x = .15),
side = "r",outlier.shape = NA, center = TRUE, errorbar.draw = FALSE, width = .2,
fill = 'darkorange') +
geom_half_violin(
data = d %>% filter(x=="1"),aes(x = x, y = y), position = position_nudge(x = -.3),
side = "l", fill = 'dodgerblue') +
geom_half_violin(
data = d %>% filter(x=="2"),aes(x = x, y = y), position = position_nudge(x = .3),
side = "r", fill = "darkorange") +
#Define additional settings
scale_x_continuous(breaks=c(1,2), labels=c("Pre-Test", "Post-Test"), limits=c(0, 3)) +
xlab("Test") + ylab("Score") +
ggtitle("Before and After Scores with box- and violin plots") +
theme_classic()+
coord_cartesian(ylim=c(y_lim_min, y_lim_max))
I am trying to draw a forest plot with different groups. The code I'm using looks like the following:
d = data.frame(Estimate = c(1.8,1.9,2.1,2.4,2.7,2.5),
Group = rep(c('Group A', 'Group B'), each = 3),
Method = rep(c('Method 1', 'Method 2', 'Method 3'), 2))
d$Lower = d$Estimate - 0.3
d$Upper = d$Estimate + 0.3
ggplot(data = d, aes(y = Group, x = Estimate, xmin = Lower, xmax = Upper, color = Method)) +
geom_point(size = 2, position=position_dodge(width = 0.5)) +
geom_linerange(position=position_dodge(width = 0.5)) +
geom_vline(xintercept = c(2, 2.5), linetype = "dashed")
And the resulting plot:
The vertical lines (2, 2.5) are the true group means. I want to limit these vertical lines to be within each group (i.e., the first one from bottom to the middle, the second one middle to top). Anyone know how to do this?
I've tried geom_segment() function but I think it requires a numerical y input, while it's a factor here.
Factors plotted on an axis are "really" numeric, but with labels added, so you can go ahead and add numeric segments:
ggplot(data = d, aes(y = Group, x = Estimate, xmin = Lower, xmax = Upper,
color = Method)) +
geom_point(size = 2, position=position_dodge(width = 0.5)) +
geom_linerange(position=position_dodge(width = 0.5)) +
geom_segment(data = data.frame(y = c(0.67, 1.67), x = c(2, 2.5),
xend = c(2, 2.5), yend = c(1.33, 2.33)),
aes(x, y, xend = xend, yend = yend),
inherit.aes = FALSE, linetype = 2)
Or, with a few tweaks:
ggplot(data = d, aes(y = Group, x = Estimate, xmin = Lower, xmax = Upper,
color = Method)) +
geom_linerange(position=position_dodge(width = 0.5), size = 1) +
geom_point(size = 3, position=position_dodge(width = 0.5), shape = 21,
fill = "white") +
geom_segment(data = data.frame(y = c(0.67, 1.67), x = c(2, 2.5),
xend = c(2, 2.5), yend = c(1.33, 2.33)),
aes(x, y, xend = xend, yend = yend),
inherit.aes = FALSE, linetype = 2) +
annotate("text", c(2, 2.5), c(1.5, 2.5), size = 6,
label = c("Group mean = 2", "Group mean = 2.5")) +
theme_minimal(base_size = 20) +
scale_color_brewer(palette = "Set1")
I was trying to plot tweets' sources/devices in a decreasing order using ggplot/geom_segment in R.
Here is the code I ran:
ggplot(data = device, mapping = aes(x = fct_reorder(as.factor(source), n), y = n)) +
geom_segment(aes(x = source, xend = source, y = 0, yend = n)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1, family = "sans")) +
labs(title = "Tweets by device/source", x = "device/source", y = "frequency") +
geom_point(size = 4, color = "red", fill = alpha("yellow", 0.3), alpha = 0.7, shape = 21, stroke = 2)
Here is the plot it returned, which is not in decreasing pattern as I wanted to be.
So, I was wondering how could I plot the geom_segment in decreasing order?
You used the correct approach, but at the wrong spot. Try to do the factor rearrangement on your data before the ggplot call. In your case you did the reordering, but then used the original "source" data and not the reordered one in geom_segment. Doing the reordering before the ggplot call fixes that.
Here is an example using the mtcars dataset:
mtcars %>%
rownames_to_column("model") %>%
as_tibble() %>%
mutate(model = fct_reorder(model, -mpg)) %>%
ggplot() +
geom_segment(aes(x = model, xend = model, y = 0, yend = mpg)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1, family = "sans")) +
labs(title = "Tweets by device/source", x = "device/source", y = "frequency") +
geom_point(aes(x = model, y = mpg), size = 4, color = "red", fill = alpha("yellow", 0.3), alpha = 0.7, shape = 21, stroke = 2)
The new plot looks like this:
The improved code:
device %>%
as_tibble() %>%
mutate(source = fct_reorder(source, -n)) %>%
ggplot() +
geom_segment(aes(x = source, xend = source, y = 0, yend = n)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1, family = "sans", size = 10)) +
labs(title = "Tweets by device/source", x = "device/source", y = "frequency") +
geom_point(aes(x = source, y = n), size = 3, color = "red", fill =
alpha("yellow", 0.3), alpha = 0.7, shape = 21, stroke = 2)
Here is a data frame:
library(tidyverse)
example_df <- structure(list(Funnel = c("Sessions", "AddToCart", "Registrations", "ShippingDetails", "Checkout", "Transactions"), Sum = c(1437574, 385281, 148181, 56989, 35613, 29671), End = c(NA, 1437574, 385281, 148181, 56989, 35613), xpos = c(0.5, 1.5, 2.5, 3.5, 4.5, 5.5), Diff = c(NA, 1052293, 237100, 91192, 21376, 5942), Percent = c("NA %", "73.2 %", "61.5 %", "61.5 %", "37.5 %", "16.7 %")), .Names = c("Funnel", "Sum", "End", "xpos", "Diff", "Percent"), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L))
And here is a ggplot2:
ggplot(example_df, aes(x = reorder(Funnel, -Sum), y = Sum)) +
geom_col(alpha = 0.6, fill = "#008080") +
stat_summary(aes(label = scales::comma(..y..)), fun.y = 'sum',
geom = 'text', col = 'white', vjust = 1.5) +
geom_segment(aes(x=xpos, y = End, xend = xpos, yend = Sum)) +
geom_text(aes(x=xpos,y = End-Diff / 2, label=Percent), hjust = -0.2) +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) +
scale_y_continuous(labels = function(l) {l = l / 1000; paste0(l, "K")}) +
Here's what it looks like:
The values on the plot from Shipping Details: Transactions are tricky to read because the bars are smaller.
I wondered if there was a good approach to dealing with this. I tried extending the range with:
+ expand_limits(y = -100000)
But that just lowers the y axis.
Is there a sensible solution to visualizing the data points in a way they are not squished? If I could somehow lower the green bars into the minus region without impacting the proportions?
Very dirty solution, but works. Add dummy geom_bar's bellow each segment (ie., extend original segment by adding negative bar) with the same color and alpha.
Bars to add:
geom_bar(data = data.frame(x = example_df$Funnel, y = -2e4),
aes(x, y),
stat = "identity", position = "dodge",
alpha = 0.6, fill = "#008080")
Final code:
# Using OPs data
library(ggplot2)
ggplot(example_df, aes(x = reorder(Funnel, -Sum), y = Sum)) +
geom_col(alpha = 0.6, fill = "#008080") +
geom_segment(aes(x=xpos, y = End, xend = xpos, yend = Sum)) +
geom_text(aes(x=xpos,y = End-Diff / 2, label=Percent), hjust = -0.2) +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) +
scale_y_continuous(labels = function(l) {l = l / 1000; paste0(l, "K")}) +
geom_bar(data = data.frame(x = example_df$Funnel, y = -2e4),
aes(x, y),
stat = "identity", position = "dodge",
alpha = 0.6, fill = "#008080") +
stat_summary(aes(label = scales::comma(..y..)), fun.y = 'sum',
geom = 'text', col = 'white', vjust = 1.5) +
theme_classic()
Plot:
PS:
You have to add stat_summary after geom_bar