Hi and thanks for reading me
I am working with a pie bar chart in ggplot2 and I would like to make it interactive with Ggiraph, but I am not getting this to happen and I do not understand what I am doing wrong, or if it is not possible for this particular case. Anyone know if there is any solution about it?
The code is the following:
data <- data.frame(
stringsAsFactors = FALSE,
individual = c("INDUSTRIAL","DE COMERCIO INTERIOR",
"DE COMERCIO EXTERIOR",
"DE ATRACCION DE INVERSION EXTRANJERA",
"POLĂTICA DE DESARROLLO PARA LA COMPETITIVIDAD DE LAS MIPYMES","DE MEJORA REGULATORIA",
"EN MATERIA MINERA","DE ABASTO","DE PRECIOS",
"DE PROTECCION AL CONSUMIDOR",
"NACIONAL DE CALIDAD",
"NACIONAL EN MATERIA DE NORMALIZACION, ESTANDARIZACION, EVALUACION DE LA",
"CONFORMIDAD Y METROLOGIA",
"DE INDUSTRIALIZACION, DISTRIBUCION Y CONSUMO DE LOS PRODUCTOS AGRICOLAS, GANADEROS, FORESTALES, MINERALES Y PESQUEROS",
"NACIONAL DE FOMENTO ECONOMICO",
"PARA CREAR Y APOYAR EMPRESAS QUE ASOCIEN A GRUPOS DE ESCASOS RECURSOS EN AREAS URBANAS"),
group = c("A","A","A","A","B","B","B","B",
"B","B","B","C","C","C","C","C"),
value1 = c(30L,3L,7L,3L,0L,3L,1L,2L,0L,1L,
7L,5L,1L,12L,0L,4L),
value2 = c(10L,0L,2L,0L,0L,6L,0L,0L,0L,11L,
7L,6L,0L,3L,1L,0L),
value3 = c(0L,0L,1L,2L,14L,2L,1L,0L,0L,0L,
1L,1L,0L,2L,0L,0L),
value4 = c(9L,0L,13L,8L,2L,5L,1L,1L,0L,0L,
0L,1L,2L,2L,0L,0L)
)
data = data %>%
gather(key = "observation", value="value", -c(1,2))
empty_bar=2
nObsType=nlevels(as.factor(data$observation))
to_add = data.frame( matrix(NA, empty_bar*nlevels(data$group)*nObsType, ncol(data)) )
colnames(to_add) = colnames(data)
to_add$group=rep(levels(data$group), each=empty_bar*nObsType )
data=rbind(data, to_add)
data=data %>% arrange(group, individual)
data$id=rep( seq(1, nrow(data)/nObsType) , each=nObsType)
# Get the name and the y position of each label
label_data= data %>% group_by(id, individual) %>% summarize(tot=sum(value))
number_of_bar=nrow(label_data)
angle= 90 - 360 * (label_data$id-0.5) /number_of_bar # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_data$hjust<-ifelse( angle < -90, 1, 0)
label_data$angle<-ifelse(angle < -90, angle+180, angle)
# prepare a data frame for base lines
base_data=data %>%
group_by(group) %>%
summarize(start=min(id), end=max(id) - empty_bar) %>%
rowwise() %>%
mutate(title=mean(c(start, end)))
# prepare a data frame for grid (scales)
grid_data = base_data
grid_data$end = grid_data$end[ c( nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start = grid_data$start - 1
grid_data=grid_data[-1,]
rhg_cols <- c("#12A09A", "#1E5C4F", "#941B80", "#F19100")
# Make the plot
p <- ggplot(data) +
# Add the stacked bar
ggiraph::geom_bar_interactive(aes(x=as.factor(id), y=value, fill=observation), stat="identity", alpha=0.5) +
#scale_fill_viridis(discrete=TRUE) +
scale_fill_manual(values = rhg_cols)+
# Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
geom_segment(data=grid_data, aes(x = end, y = 0, xend = start, yend = 0), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 50, xend = start, yend = 50), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 100, xend = start, yend = 100), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 150, xend = start, yend = 150), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 200, xend = start, yend = 200), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
# Add text showing the value of each 100/75/50/25 lines
annotate("text", x = rep(max(data$id),5), y = c(0, 50, 100, 150, 200), label = c("0", "50", "100", "150", "200") , color="grey", size=2 , angle=0, fontface="bold", hjust=1) +
ylim(-25,max(label_data$tot, na.rm=T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1,4), "cm")
) +
coord_polar() +
# Add labels on top of each bar
geom_text(data=label_data, aes(x=id, y=tot+3, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=2, angle= label_data$angle, inherit.aes = FALSE )
# Add base line information
#geom_segment(data=base_data, aes(x = start, y = -5, xend = end, yend = -5), colour = "black", alpha=0.8, size=0.6 , inherit.aes = FALSE )
#geom_text(data=base_data, aes(x = title, y = -18, label=group), hjust=c(1,1,0,0), colour = "black", alpha=0.8, size=4, fontface="bold", inherit.aes = FALSE)
p
# interactive plot
girafe(
ggobj = p,
width_svg = 7, height_svg = 4, bg = "#D7E0DA",
options = list(
opts_hover(css = "fill:#5eba7d88;cursor:pointer;"),
opts_hover_theme(css = "fill:red;cursor:pointer;"),
opts_selection(css = "fill:#5eba7d;cursor:pointer;", only_shiny = FALSE, selected = "J"),
opts_tooltip(css = "background-color:white;padding:5px;border-radius:2px;border: black 1px solid;color:black;")
)
)
UPDATE
Now I use geom_col (geom_col_interactive) but when I exported the object to girafe() nothing appears in the viewfinder
The code is the following:
p <- ggplot(data) +
geom_col_interactive(aes(x=as.factor(id), y=value, fill=observation), stat="identity", alpha=0.5) +
scale_fill_manual_interactive(values = rhg_cols)+
annotate("text", x = rep(max(data$id),5), y = c(0, 50, 100, 150, 200), label = c("0", "50", "100", "150", "200") ,
color="grey", size=2 , angle=0, fontface="bold", hjust=1) +
ylim(-25,max(label_data$tot, na.rm=T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1,4), "cm")
) +
coord_polar() +
geom_text_interactive(data=label_data, aes(x=id, y=tot+3, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6,
size=2, angle= label_data$angle, inherit.aes = FALSE )
p
girafe(
ggobj = p,
width_svg = 7, height_svg = 4, bg = "#D7E0DA",
options = list(
opts_hover(css = "fill:#5eba7d88;cursor:pointer;"),
opts_hover_theme(css = "fill:red;cursor:pointer;"),
opts_selection(css = "fill:#5eba7d;cursor:pointer;", only_shiny = FALSE, selected = "J"),
opts_tooltip(css = "background-color:white;padding:5px;border-radius:2px;border: black 1px solid;color:black;")
)
)
There are ggplot issues in your code, for example, geom_bar should not be used with a y, use geom_col instead.
With a simple example, here is how to do (from https://www.r-graph-gallery.com/128-ring-or-donut-plot.html)
# load library
library(ggplot2)
library(ggiraph)
# Create test data.
data <- data.frame(
category=c("A", "B", "C"),
count=c(10, 60, 30)
)
# Compute percentages
data$fraction = data$count / sum(data$count)
# Compute the cumulative percentages (top of each rectangle)
data$ymax = cumsum(data$fraction)
# Compute the bottom of each rectangle
data$ymin = c(0, head(data$ymax, n=-1))
# Make the plot
p <- ggplot(data, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=category)) +
geom_rect_interactive(aes(tooltip = paste(category,count), data_id = category)) +
coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially
xlim(c(2, 4)) # Try to remove that to see how to make a pie chart
girafe(
ggobj = p,
width_svg = 7, height_svg = 4, bg = "#D7E0DA",
options = list(
opts_hover(css = "fill:#5eba7d88;cursor:pointer;"),
opts_hover_theme(css = "fill:red;cursor:pointer;"),
opts_selection(css = "fill:#5eba7d;cursor:pointer;", only_shiny = FALSE, selected = "J"),
opts_tooltip(css = "background-color:white;padding:5px;border-radius:2px;border: black 1px solid;color:black;")
)
)
Related
This question already has an answer here:
Circular barchart customization from r-graph-gallery
(1 answer)
Closed 8 months ago.
I am trying to run this code from this link https://www.r-graph-gallery.com/299-circular-stacked-barplot.html.
# library
library(tidyverse)
library(viridis)
# Create dataset
data <- data.frame(
individual=paste( "Mister ", seq(1,60), sep=""),
group=c( rep('A', 10), rep('B', 30), rep('C', 14), rep('D', 6)) ,
value1=sample( seq(10,100), 60, replace=T),
value2=sample( seq(10,100), 60, replace=T),
value3=sample( seq(10,100), 60, replace=T)
)
# Transform data in a tidy format (long format)
data <- data %>% gather(key = "observation", value="value", -c(1,2))
# Set a number of 'empty bar' to add at the end of each group
empty_bar <- 2
nObsType <- nlevels(as.factor(data$observation))
to_add <- data.frame( matrix(NA, empty_bar*nlevels(data$group)*nObsType, ncol(data)) )
colnames(to_add) <- colnames(data)
to_add$group <- rep(levels(data$group), each=empty_bar*nObsType )
data <- rbind(data, to_add)
data <- data %>% arrange(group, individual)
data$id <- rep( seq(1, nrow(data)/nObsType) , each=nObsType)
# Get the name and the y position of each label
label_data <- data %>% group_by(id, individual) %>% summarize(tot=sum(value))
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id-0.5) /number_of_bar # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_data$hjust <- ifelse( angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle+180, angle)
# prepare a data frame for base lines
base_data <- data %>%
group_by(group) %>%
summarize(start=min(id), end=max(id) - empty_bar) %>%
rowwise() %>%
mutate(title=mean(c(start, end)))
# prepare a data frame for grid (scales)
grid_data <- base_data
grid_data$end <- grid_data$end[ c( nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1,]
# Make the plot
p <- ggplot(data) +
# Add the stacked bar
geom_bar(aes(x=as.factor(id), y=value, fill=observation), stat="identity", alpha=0.5) +
scale_fill_viridis(discrete=TRUE) +
# Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
geom_segment(data=grid_data, aes(x = end, y = 0, xend = start, yend = 0), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 50, xend = start, yend = 50), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 100, xend = start, yend = 100), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 150, xend = start, yend = 150), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 200, xend = start, yend = 200), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
# Add text showing the value of each 100/75/50/25 lines
ggplot2::annotate("text", x = rep(max(data$id),5), y = c(0, 50, 100, 150, 200), label = c("0", "50", "100", "150", "200") , color="grey", size=6 , angle=0, fontface="bold", hjust=1) +
ylim(-150,max(label_data$tot, na.rm=T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1,4), "cm")
) +
coord_polar() +
# Add labels on top of each bar
geom_text(data=label_data, aes(x=id, y=tot+10, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=5, angle= label_data$angle, inherit.aes = FALSE ) +
# Add base line information
geom_segment(data=base_data, aes(x = start, y = -5, xend = end, yend = -5), colour = "black", alpha=0.8, size=0.6 , inherit.aes = FALSE ) +
geom_text(data=base_data, aes(x = title, y = -18, label=group), hjust=c(1,1,0,0), colour = "black", alpha=0.8, size=4, fontface="bold", inherit.aes = FALSE)
# Save at png
ggsave(p, file="output.png", width=10, height=10)
However, I am not sure why I am not getting the gaps and the scales in my figure (see below). As depicted, the numbers are printed inside the figure and the gaps between different groups of data are not there.
The original figure should be as follows:
There is a bug in the code. group has to be a factor to make the code adding the gaps work. To fix this add data$group <- factor(data$group).
Note: My guess is that the reason for this bug is that as of version 4.0.0 R treats strings in data frames as strings rather than factors. Hence, for versions < 4.0.0 the code worked fine as is.
# library
library(tidyverse)
library(viridis)
#> Loading required package: viridisLite
# Create dataset
data <- data.frame(
individual = paste("Mister ", seq(1, 60), sep = ""),
group = c(rep("A", 10), rep("B", 30), rep("C", 14), rep("D", 6)),
value1 = sample(seq(10, 100), 60, replace = T),
value2 = sample(seq(10, 100), 60, replace = T),
value3 = sample(seq(10, 100), 60, replace = T)
)
# Convert to factor
data$group <- factor(data$group)
# Transform data in a tidy format (long format)
data <- data %>% gather(key = "observation", value = "value", -c(1, 2))
# Set a number of 'empty bar' to add at the end of each group
empty_bar <- 2
nObsType <- nlevels(as.factor(data$observation))
to_add <- data.frame(matrix(NA, empty_bar * nlevels(data$group) * nObsType, ncol(data)))
colnames(to_add) <- colnames(data)
to_add$group <- rep(levels(data$group), each = empty_bar * nObsType)
data <- rbind(data, to_add)
data <- data %>% arrange(group, individual)
data$id <- rep(seq(1, nrow(data) / nObsType), each = nObsType)
# Get the name and the y position of each label
label_data <- data %>%
group_by(id, individual) %>%
summarize(tot = sum(value))
#> `summarise()` has grouped output by 'id'. You can override using the `.groups`
#> argument.
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id - 0.5) / number_of_bar # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_data$hjust <- ifelse(angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle + 180, angle)
# prepare a data frame for base lines
base_data <- data %>%
group_by(group) %>%
summarize(start = min(id), end = max(id) - empty_bar) %>%
rowwise() %>%
mutate(title = mean(c(start, end)))
# prepare a data frame for grid (scales)
grid_data <- base_data
grid_data$end <- grid_data$end[c(nrow(grid_data), 1:nrow(grid_data) - 1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1, ]
# Make the plot
ggplot(data) +
# Add the stacked bar
geom_bar(aes(x = as.factor(id), y = value, fill = observation), stat = "identity", alpha = 0.5) +
scale_fill_viridis(discrete = TRUE) +
# Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
geom_segment(data = grid_data, aes(x = end, y = 0, xend = start, yend = 0), colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
geom_segment(data = grid_data, aes(x = end, y = 50, xend = start, yend = 50), colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
geom_segment(data = grid_data, aes(x = end, y = 100, xend = start, yend = 100), colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
geom_segment(data = grid_data, aes(x = end, y = 150, xend = start, yend = 150), colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
geom_segment(data = grid_data, aes(x = end, y = 200, xend = start, yend = 200), colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
# Add text showing the value of each 100/75/50/25 lines
ggplot2::annotate("text", x = rep(max(data$id), 5), y = c(0, 50, 100, 150, 200), label = c("0", "50", "100", "150", "200"), color = "grey", size = 6, angle = 0, fontface = "bold", hjust = 1) +
ylim(-150, max(label_data$tot, na.rm = T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1, 4), "cm")
) +
coord_polar() +
# Add labels on top of each bar
geom_text(data = label_data, aes(x = id, y = tot + 10, label = individual, hjust = hjust), color = "black", fontface = "bold", alpha = 0.6, size = 5, angle = label_data$angle, inherit.aes = FALSE) +
# Add base line information
geom_segment(data = base_data, aes(x = start, y = -5, xend = end, yend = -5), colour = "black", alpha = 0.8, size = 0.6, inherit.aes = FALSE) +
geom_text(data = base_data, aes(x = title, y = -18, label = group), hjust = c(1, 1, 0, 0), colour = "black", alpha = 0.8, size = 4, fontface = "bold", inherit.aes = FALSE)
#> Warning: Removed 24 rows containing missing values (position_stack).
#> Warning: Removed 9 rows containing missing values (geom_text).
I have created a plot with geom_area(), geom_line() in it. Now I would like to add a country map background in the plot and for same I am trying to use: map_data() & geom_ploygon() but it's giving error, probably because one's xaxis is on date scale & other's is longitude.
Error:
Error: Invalid input: date_trans works with objects of class Date only
Here is my code & plot without map:
library(tidyverse)
library(glue)
library(scales)
library(tidytext)
data:
file_url <- "https://raw.githubusercontent.com/johnsnow09/covid19-df_stack-code/main/ts_all_long3.csv"
ts_all_long <- read.csv(url(file_url))
Step 1:
confirm_col = "#32a4ba"
death_col = "#f08080"
Country_selected = c("India")
scaleFactor = max(ts_all_long %>%
filter(Country.Region %in% Country_selected) %>%
pull(Confirmed_daily)) /
max(ts_all_long %>%
filter(Country.Region %in% Country_selected) %>%
pull(Death_daily))
ts_all_long %>%
filter(Country.Region %in% c("India") ) %>%
ggplot(aes(x = date)) +
geom_area(aes(y = Confirmed_daily), fill = confirm_col, alpha = .7) +
geom_line(aes(y = Death_daily * scaleFactor), col = death_col,
size = 0.8, alpha = 0.8) +
scale_y_continuous(name = "Daily Cases", sec.axis = sec_axis(~./scaleFactor, name = "Daily Deaths"),
labels = scales::comma_format()) +
scale_x_date(date_breaks = "1 month", date_labels = "%b") +
geom_hline(yintercept = c(25000,95000), lty = 2, col = "grey50") +
geom_vline(xintercept = c(ymd("2020-07-08"),ymd("2020-09-10"),
ymd("2021-03-15"),ymd("2021-04-03")),
lty = 2, col = "grey50") +
annotate("text", x = ymd("2020-08-10"), y = 96000, col = death_col, size = 3,
label = "25k to 95k in \n~2months+") +
annotate("text", x = ymd("2021-03-18"), y = 96000, col = death_col, size = 3,
label = "25k to 95k in \n~2weeks+") +
geom_text(
label=glue("1st wave"), angle = 90, x=ymd("2020-07-30"), y= 75000,
size = 4, color = confirm_col
) +
geom_text(
label=glue("2nd wave"), angle = 90, x=ymd("2021-03-18"), y= 75000,
size = 4, color = confirm_col
) +
theme_excel_new() +
theme(
axis.title.y.left=element_text(color=confirm_col),
axis.text.y.left=element_text(color=confirm_col),
axis.title.y.right=element_text(color=death_col),
axis.text.y.right=element_text(color=death_col),
plot.title = element_markdown(face = "plain", family = "serif", size = 14),
panel.grid.major = element_blank()
) +
labs(title = glue("<i>{Country_selected}</i>: Daily Cases to jump to 1 lac in 1st & 2nd wave, as of: {max(ts_all_long$date)}"),
# subtitle = "Cases to jump from 25,000 to 95,000 in first & second wave",
caption = "Data source: covid19.analytics
Created by: ViSa")
Step 2: Code & image for map:
ggplot() +
geom_polygon(data = map_data("world", region = "India"),
aes(x = long, y = lat, group = group),
fill="lightgray", colour = "white")
Step 3: When I try to combine code for above 2 steps I get an error:
confirm_col = "#32a4ba"
death_col = "#f08080"
Country_selected = c("India")
scaleFactor = max(ts_all_long %>%
filter(Country.Region %in% Country_selected) %>%
pull(Confirmed_daily)) /
max(ts_all_long %>%
filter(Country.Region %in% Country_selected) %>%
pull(Death_daily))
ts_all_long %>%
filter(Country.Region %in% c("India") ) %>%
ggplot() +
# added country map here from step2
geom_polygon(data = map_data("world", region = "India"),
aes(x = long, y = lat, group = group),
fill="lightgray", colour = "white") +
# usual plot of step1
geom_area(aes(x = date, y = Confirmed_daily), fill = confirm_col, alpha = .7) +
geom_line(aes(x = date, y = Death_daily * scaleFactor), col = death_col,
size = 0.8, alpha = 0.8) +
scale_y_continuous(name = "Daily Cases", sec.axis = sec_axis(~./scaleFactor, name = "Daily Deaths"),
labels = scales::comma_format()) +
scale_x_date(date_breaks = "1 month", date_labels = "%b") +
geom_hline(yintercept = c(25000,95000), lty = 2, col = "grey50") +
geom_vline(xintercept = c(ymd("2020-07-08"),ymd("2020-09-10"),
ymd("2021-03-15"),ymd("2021-04-03")),
lty = 2, col = "grey50") +
annotate("text", x = ymd("2020-08-10"), y = 96000, col = death_col, size = 3,
label = "25k to 95k in \n~2months+") +
annotate("text", x = ymd("2021-03-18"), y = 96000, col = death_col, size = 3,
label = "25k to 95k in \n~2weeks+") +
geom_text(
label=glue("1st wave"), angle = 90, x=ymd("2020-07-30"), y= 75000,
size = 4, color = confirm_col
) +
geom_text(
label=glue("2nd wave"), angle = 90, x=ymd("2021-03-18"), y= 75000,
size = 4, color = confirm_col
) +
theme_excel_new() +
theme(
axis.title.y.left=element_text(color=confirm_col),
axis.text.y.left=element_text(color=confirm_col),
axis.title.y.right=element_text(color=death_col),
axis.text.y.right=element_text(color=death_col),
plot.title = element_markdown(face = "plain", family = "serif", size = 14),
panel.grid.major = element_blank()
) +
labs(title = glue("<i>{Country_selected}</i>: Daily Cases to jump to 1 lac in 1st & 2nd wave, as of: {max(ts_all_long$date)}"),
# subtitle = "Cases to jump from 25,000 to 95,000 in first & second wave",
caption = "Data source: covid19.analytics
Created by: ViSa")
I would suggest to add the map as a background image to your plot which could be done via e.g. the ggimage package like so:
library(ggimage)
map <- ggplot() +
geom_polygon(data = map_data("world", region = "India"),
aes(x = long, y = lat, group = group),
fill="lightgray", colour = "white") +
theme_void()
ggsave("map.png")
#> Saving 7 x 5 in image
ggbackground(p, "map.png")
p:
d <- ts_all_long %>%
filter(Country.Region %in% c("India")) %>%
mutate(date = as.Date(date))
p <- ggplot(d, aes(x = date)) +
geom_area(aes(y = Confirmed_daily), fill = confirm_col, alpha = .7) +
geom_line(aes(y = Death_daily * scaleFactor), col = death_col,
size = 0.8, alpha = 0.8) +
scale_y_continuous(name = "Daily Cases", sec.axis = sec_axis(~./scaleFactor, name = "Daily Deaths"),
labels = scales::comma_format()) +
scale_x_date(date_breaks = "1 month", date_labels = "%b") +
geom_hline(yintercept = c(25000,95000), lty = 2, col = "grey50") +
geom_vline(xintercept = c(ymd("2020-07-08"),ymd("2020-09-10"),
ymd("2021-03-15"),ymd("2021-04-03")),
lty = 2, col = "grey50") +
annotate("text", x = ymd("2020-08-10"), y = 96000, col = death_col, size = 3,
label = "25k to 95k in \n~2months+") +
annotate("text", x = ymd("2021-03-18"), y = 96000, col = death_col, size = 3,
label = "25k to 95k in \n~2weeks+") +
geom_text(
label=glue("1st wave"), angle = 90, x=ymd("2020-07-30"), y= 75000,
size = 4, color = confirm_col
) +
geom_text(
label=glue("2nd wave"), angle = 90, x=ymd("2021-03-18"), y= 75000,
size = 4, color = confirm_col
) +
theme_excel_new() +
theme(
axis.title.y.left=element_text(color=confirm_col),
axis.text.y.left=element_text(color=confirm_col),
axis.title.y.right=element_text(color=death_col),
axis.text.y.right=element_text(color=death_col),
plot.title = element_markdown(face = "plain", family = "serif", size = 14),
panel.grid.major = element_blank()
) +
labs(title = glue("<i>{Country_selected}</i>: Daily Cases to jump to 1 lac in 1st & 2nd wave, as of: {max(ts_all_long$date)}"),
# subtitle = "Cases to jump from 25,000 to 95,000 in first & second wave",
caption = "Data source: covid19.analytics
Created by: ViSa")
I got an error in R, when tried to plot the circular barplot. This is the error - Error: Aesthetics must be either length 1 or the same as the data (9):
This is the structure of my data, just limited one:
structure(list(Symptom = c("Chills", "Chills", "Chills", "Cough",
"Cough", "Cough"), Morbidity = c("Asthma (managed with an inhaler)",
"Asthma (managed with an inhaler)", "Asthma (managed with an inhaler)",
"Asthma (managed with an inhaler)", "Asthma (managed with an inhaler)",
"Asthma (managed with an inhaler)"), Severity = c("Mild", "Moderate",
"Severe", "Mild", "Moderate", "Severe"), Count = c(264L, 53L,
19L, 853L, 158L, 27L), id = c(1L, 1L, 1L, 2L, 2L, 2L)), row.names = c(NA,
6L), class = "data.frame")
And this is what I how I tried to plot:
gather_divided <- data.frame(gather_divided)
gather_divided <- gather_divided %>%
dplyr::select(Symptom, Morbidity, Severity, Count)
# Set a number of 'empty bar' to add at the end of each group
empty_bar <- 2
nObsType <- nlevels(as.factor(gather_divided$Severity))
nObsType
to_add <- data.frame(matrix(NA, empty_bar*nlevels(gather_divided$Morbidity)*nObsType, ncol(gather_divided)) )
colnames(to_add) <- colnames(gather_divided)
to_add$Morbidity <- rep(levels(gather_divided$Morbidity), each=empty_bar*nObsType )
gather_divided <- rbind(gather_divided, to_add)
gather_divided <- gather_divided %>% arrange(Morbidity, Symptom)
gather_divided$id <- rep( seq(1, nrow(gather_divided)/nObsType) , each=nObsType)
# Get the name and the y position of each label
label_data <- gather_divided %>% group_by(id, Symptom) %>% summarize(tot=sum(Count))
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id-0.5) /number_of_bar # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_data$hjust <- ifelse( angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle+180, angle)
# prepare a data frame for base lines
base_data <- gather_divided %>%
group_by(Morbidity) %>%
summarize(start=min(id), end=max(id) - empty_bar) %>%
rowwise() %>%
mutate(title=mean(c(start, end)))
# prepare a data frame for grid (scales)
grid_data <- base_data
grid_data$end <- grid_data$end[ c( nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1,]
# Make the plot
p <- ggplot(gather_divided) +
# Add the stacked bar
geom_bar(aes(x=as.factor(id), y=Count, fill=Morbidity), stat="identity", alpha=0.5) +
scale_fill_viridis(discrete=TRUE) +
# Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
geom_segment(data=grid_data, aes(x = end, y = 0, xend = start, yend = 0), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 500, xend = start, yend = 500), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 1000, xend = start, yend = 1000), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 1500, xend = start, yend = 1500), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 2000, xend = start, yend = 2000), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
# Add text showing the value of each 100/75/50/25 lines
ggplot2::annotate("text", x = rep(max(gather_divided$id),5), y = c(0, 500, 1000, 1500, 2000),
label = c("0", "500", "1000", "1500", "2000") , color="grey", size=6 , angle=0, fontface="bold", hjust=1) +
ylim(-150,max(label_data$tot, na.rm=T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1,4), "cm")
) +
coord_polar() +
# Add labels on top of each bar
geom_text(data=label_data, aes(x=id, y=tot+10, label= Symptom, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=5, angle= label_data$angle, inherit.aes = FALSE ) +
# Add base line information
geom_segment(data=base_data, aes(x = start, y = -5, xend = end, yend = -5), colour = "black", alpha=0.8, size=0.6 , inherit.aes = FALSE ) +
geom_text(data=base_data, aes(x = title, y = -18, label=Morbidity), hjust=c(1,1,0,0), colour = "black", alpha=0.8, size=4, fontface="bold", inherit.aes = FALSE)
p
Did someone else tried to plot a circular marplot and faced the same issue? How to solve this issue? I am hoping to solve it. Thank you in advance for this.
I try to run the code for a circular barplot provided by https://www.r-graph-gallery.com/299-circular-stacked-barplot.html
# library
library(tidyverse)
library(viridis)
# Create dataset
data <- data.frame(
individual=paste( "Mister ", seq(1,60), sep=""),
group=c( rep('A', 10), rep('B', 30), rep('C', 14), rep('D', 6)) ,
value1=sample( seq(10,100), 60, replace=T),
value2=sample( seq(10,100), 60, replace=T),
value3=sample( seq(10,100), 60, replace=T)
)
# Transform data in a tidy format (long format)
data <- data %>% gather(key = "observation", value="value", -c(1,2))
# Set a number of 'empty bar' to add at the end of each group
empty_bar <- 2
nObsType <- nlevels(as.factor(data$observation))
to_add <- data.frame( matrix(NA, empty_bar*nlevels(data$group)*nObsType, ncol(data)) )
colnames(to_add) <- colnames(data)
to_add$group <- rep(levels(data$group), each=empty_bar*nObsType )
data <- rbind(data, to_add)
data <- data %>% arrange(group, individual)
data$id <- rep( seq(1, nrow(data)/nObsType) , each=nObsType)
# Get the name and the y position of each label
label_data <- data %>% group_by(id, individual) %>% summarize(tot=sum(value))
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id-0.5) /number_of_bar # I substract 0.5 because the letter must have the angle of the center of the bars. Not extreme right(1) or extreme left (0)
label_data$hjust <- ifelse( angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle+180, angle)
# prepare a data frame for base lines
base_data <- data %>%
group_by(group) %>%
summarize(start=min(id), end=max(id) - empty_bar) %>%
rowwise() %>%
mutate(title=mean(c(start, end)))
# prepare a data frame for grid (scales)
grid_data <- base_data
grid_data$end <- grid_data$end[ c( nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1,]
# Make the plot
p <- ggplot(data) +
# Add the stacked bar
geom_bar(aes(x=as.factor(id), y=value, fill=observation), stat="identity", alpha=0.5) +
scale_fill_viridis(discrete=TRUE) +
# Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
geom_segment(data=grid_data, aes(x = end, y = 0, xend = start, yend = 0), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 50, xend = start, yend = 50), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 100, xend = start, yend = 100), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 150, xend = start, yend = 150), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
geom_segment(data=grid_data, aes(x = end, y = 200, xend = start, yend = 200), colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE ) +
# Add text showing the value of each 100/75/50/25 lines
ggplot2::annotate("text", x = rep(max(data$id),5), y = c(0, 50, 100, 150, 200), label = c("0", "50", "100", "150", "200") , color="grey", size=6 , angle=0, fontface="bold", hjust=1) +
ylim(-150,max(label_data$tot, na.rm=T)) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-1,4), "cm")
) +
coord_polar() +
# Add labels on top of each bar
geom_text(data=label_data, aes(x=id, y=tot+10, label=individual, hjust=hjust), color="black", fontface="bold",alpha=0.6, size=5, angle= label_data$angle, inherit.aes = FALSE ) +
# Add base line information
geom_segment(data=base_data, aes(x = start, y = -5, xend = end, yend = -5), colour = "black", alpha=0.8, size=0.6 , inherit.aes = FALSE ) +
geom_text(data=base_data, aes(x = title, y = -18, label=group), hjust=c(1,1,0,0), colour = "black", alpha=0.8, size=4, fontface="bold", inherit.aes = FALSE)
# Save at png
ggsave(p, file="output.png", width=10, height=10)
Then, I ran into several error messages.
Three from running the code under
Get the name and the y position of each label
Warning message:
Factor individual contains implicit NA, consider using forcats::fct_explicit_na
Error in $<-.data.frame(*tmp*, hjust, value = logical(0)) :
replacement has 0 rows, data has 1
Error in $<-.data.frame(*tmp*, angle, value = logical(0)) :
replacement has 0 rows, data has 1
And two from
Make the plot
Warning message:
In max(label_data$tot, na.rm = T) :
no non-missing arguments to max; returning -Inf
Error: Aesthetics must be either length 1 or the same as the data (1): x, xend
Can anyone help me with these errors?
Thanks in advance
I want to plot a graph. Several of my x-axis labels have a common label. So I want to add common text as label instead of several separate labels on x-axis as shown in the attached images. How can this be done?
library(dplyr)
library(forcats)
library(ggplot2)
df <- data.frame(conc = c(0, 10, 50, 100, "Positive Control"),
values = c(3, 3, 4, 5, 10),
name = c("TiO2 NP", "TiO2 NP", "TiO2 NP", "TiO2 NP", "Cyclophosamide"))
df$conc <- as.factor(df$conc)
labels2 <- paste0(df$conc, "\n", df$name)
df %>%
mutate(conc = fct_reorder(conc, values)) %>%
ggplot(aes(x = conc, y=values, fill = conc))+
geom_bar(stat = "identity",show.legend = FALSE, width = 0.6)+
scale_x_discrete(labels = labels2)+
labs(x = "\n Dose (mg/kg BW)")
I don't think there's a simple way. You have to play with ggplot2 for some time to make something really custom. Here's my example:
df %>%
mutate(
conc = fct_reorder(conc, values),
labels2 = if_else(
name == 'TiO2 NP',
as.character(conc),
paste0(conc, '\n', name)
)
) %>%
ggplot(aes(x=conc, y=values, fill = conc)) +
geom_bar(
stat = "identity",
show.legend = FALSE,
width = 0.6
) +
geom_rect(aes(
xmin = .4,
xmax = 5.6,
ymin = -Inf,
ymax = 0
),
fill = 'white'
) +
geom_text(aes(
y = -.4,
label = labels2
),
vjust = 1,
size = 3.4,
color = rgb(.3, .3, .3)
) +
geom_line(data = tibble(
x = c(.9, 4.1),
y = c(-1.2, -1.2)
),
aes(
x = x,
y = y
),
color = rgb(.3, .3, .3),
inherit.aes = FALSE
) +
geom_curve(data = tibble(
x1 = c(.8, 4.1),
x2 = c(.9, 4.2),
y1 = c(-.8, -1.2),
y2 = c(-1.2, -.8)
),
aes(
x = x1,
y = y1,
xend = x2,
yend = y2
),
color = rgb(.3, .3, .3),
inherit.aes = FALSE
) +
geom_text(aes(
x = 2.5,
y = -1.7,
label = 'TiO2 NP'
),
size = 3.4,
color = rgb(.3, .3, .3),
check_overlap = TRUE
) +
geom_text(aes(
x = 3,
y = -2.4,
label = '\n Dose (mg/kg BW)'
),
show.legend = FALSE,
check_overlap = TRUE
) +
theme_minimal() +
theme(
axis.text.x = element_blank(),
axis.title.x = element_blank()
) +
scale_y_continuous(
breaks = seq(0, 10, 2.5),
limits = c(-2.5, 10)
)
For a more automated approach, you can try placing the common variable in facet_grid with scales = "free", space = "free", to simulate a 2nd x-axis line. The rest of the code below are for aesthetic tweaks:
df %>%
mutate(conc = fct_reorder(conc, values)) %>%
ggplot(aes(x = conc, y = values, fill = conc)) +
geom_col(show.legend = F, width = 0.6) + #geom_col() is equivalent to geom_bar(stat = "identity")
facet_grid(~ fct_rev(name),
scales = "free", space = "free",
switch = "x") + #brings the facet label positions from top (default) to bottom
scale_x_discrete(expand = c(0, 0.5)) + #adjusts the horizontal space at the ends of each facet
labs(x = "\n Dose (mg/kg BW)") +
theme(axis.line.x = element_line(arrow = arrow(ends = "both")), #show line (with arrow ends) to
#indicate facet label's extent
panel.spacing = unit(0, "cm"), #adjusts space between the facets
strip.placement = "outside", #positions facet labels below x-axis labels
strip.background = element_blank()) #transparent background for facet labels