###### tags: `R` `ggplot2::geom_linerange` `ggplot2::ggplot`

# Plot time series data

## Control multiple legends. Control top X axis breaks
**data file shared on Google drive**
[plot-data_Daily-number-containers-collected-refunded_holidays.csv](https://drive.google.com/file/d/1qKRicSeJ-fhDrUUJIRohRPivrqozIFZl/view?usp=sharing)
[plot-data_number-to-place-on-top-of-bars.csv](https://drive.google.com/file/d/1b5OR8QpWTQ2NW352Ta_3R8orwgvImGZX/view?usp=sharing)
[plot-title-data_totals.csv](https://drive.google.com/file/d/1lzLgRWjsnanGQFsc7cdA_Ex2abWtKMza/view?usp=sharing)
[plot-title-data_running-totals.csv](https://drive.google.com/file/d/1VghRsXzO-1RfjpYxk5KHJLHMLa3RI2uQ/view?usp=sharing)

**Plot**

**R code to produce the plot above**
* Problem 1: Black diamond appears in legend 1 items. How to remove them?
* Problem 2: Top X axis has duplicated weeks. How to show every week rather than every 2 weeks?

# Directory
dir.drive.C <- "C:"
dir.R <- file.path(dir.drive.C, "R")
dir.R.packages <- file.path(dir.R, "R-4.3.2") 
dir.main <- file.path(dir.drive.C,"GoogleDrive")
dir.containers <- file.path(dir.main,"containers-for-changes")
dir.output <-file.path(dir.containers,"output")

# install.packages("gsheet", lib = dir.R.packages, dependencies = TRUE)
# install.packages("ggrepel", lib = dir.R.packages, dependencies = TRUE)
# install.packages("tidyverse", lib = dir.R.packages, dependencies = TRUE)
# install.packages("ggbreak", lib = dir.R.packages, dependencies = TRUE)
# install.packages("forcats", lib = dir.R.packages, dependencies = TRUE)
# install.packages("tsibble", lib = dir.R.packages, dependencies = TRUE)
# install.packages("ggtext", lib = dir.R.packages, dependencies = TRUE)
# install.packages("hutilscpp", lib = dir.R.packages, dependencies = TRUE)

library(tzdb, lib.loc = dir.R.packages)
library(vroom, lib.loc = dir.R.packages)
library(gsheet, lib.loc = dir.R.packages)
library(stringr, lib.loc = dir.R.packages)
library(httr, lib.loc = dir.R.packages)
library(curl, lib.loc = dir.R.packages)
library(lubridate, lib.loc = dir.R.packages)
library(ggridges, lib.loc = dir.R.packages)
library(ggplot2, lib.loc = dir.R.packages)
library(labeling, lib.loc = dir.R.packages)
library(farver, lib.loc = dir.R.packages)
library(cowplot, lib.loc = dir.R.packages)
library(magick, lib.loc = dir.R.packages)
library(tidyr, lib.loc = dir.R.packages)
library(png, lib.loc = dir.R.packages)
library(jpeg, lib.loc = dir.R.packages)
library(RCurl, lib.loc = dir.R.packages)
library(grid, lib.loc = dir.R.packages)
library(ggrepel, lib.loc = dir.R.packages)
library(readr, lib.loc = dir.R.packages)
library(forcats, lib.loc = dir.R.packages)
library(tidyverse, lib.loc = dir.R.packages)
library(ggbreak, lib.loc = dir.R.packages)
library(timeDate, lib.loc = dir.R.packages)
library(tsibble, lib.loc = dir.R.packages)
library(cowplot, lib.loc = dir.R.packages)
library(ggthemes, lib.loc = dir.R.packages)
library(markdown, lib.loc = dir.R.packages)
library(xfun, lib.loc = dir.R.packages)
library(ggtext, lib.loc = dir.R.packages)
library(pals, lib.loc = dir.R.packages)
library(hutilscpp, lib.loc = dir.R.packages)

# Download shared CSV files from Google drive. Read them into R
## This is the plot data
containers.holidays.collection.days <- read.csv(
  file = file.path(dir.output,"plot-data_Daily-number-containers-collected-refunded_holidays.csv")
  ,header = TRUE) |>
  # Put date columns to Date type
  dplyr::mutate(
    date.of.activity=as.Date(date.of.activity)
  ) # dim(containers.holidays.collection.days) 168 11

## This is number data to place on top of stacked bars
totals.all.types <- read.csv(file = file.path(dir.output,"plot-data_number-to-place-on-top-of-bars.csv")
                             ,header = TRUE) |>
  # Put date columns to Date type
  dplyr::mutate(
    date.of.activity=as.Date(date.of.activity)
  ) # dim(totals.all.types) 56 4

## This is plot title data
totals <- read.csv(file = file.path(dir.output,"plot-title-data_totals.csv")
          ,header = TRUE) # dim(totals) 2 6

## This is plot title data with running totals
containers.2 <- read.csv(file=file.path(dir.output,"plot-title-data_running-totals.csv")
                         ,header = TRUE) # dim(containers.2) 115 9

# Create plot title, subtitle
plot.title.stacked.bars <- "Container collections and refunds in 2024\n"

# Function to format numbers
my_comma <- scales::label_comma(accuracy = 1, big.mark = ",", decimal.mark = ".")

plot.subtitle.stacked.bars <- paste0(totals$number.activities[1], " collections made\n"
                                     ,my_comma(totals$total[1]), " containers collected\n"
                                     ,tail(containers.2$number.stock,n=1)," containers in stock\n"
                                     ,totals$number.activities[2], " refunds received\n"
                                     ,my_comma(totals$total[2]), " containers refunded")

# bar width, position setttings
width <- .75
position <- ggplot2::position_stack(vjust=.5)

#----------
# Color
#----------
# Use a palette with multiple distinct colors
pals::pal.bands(kelly, glasbey, polychrome)
# Only 22 colors are available with 'kelly'.
# Only 32 colors are available with 'glasbey'.
# Only 36 colors are available with 'polychrome'.

# Pick first 3 color from kelly()
pals::pal.bands(glasbey(n=length(unique(containers.holidays.collection.days$container.type))))

# Display color from color code
## #8 light blue for PET, #2 red for cans, #9 brown for glass
colors <- as.vector(pals::glasbey(n=9))[c(8,2,9)]
scales::show_col(colors)

# Pair legend item and color
legend.items.color <- c( PET=colors[1]
                         ,cans=colors[2]
                         ,glass=colors[3])

# Order legend item
plot.legend.ordered <- c("PET","cans","glass") # length(plot.legend.ordered) 3
plot.legend.label.ordered <- c("PET bottles","Cans","Glass bottles") # length(plot.legend.ordered) 3

# Caption
caption <- paste0("Data source: container-collection-refund-responses.gsheet\n"
                  ,"Colour palette: pals::glasbey\n"
                  ,"Script file: containers-collected-refund.R")

# Make stacked bar plot with two legends
## Legend 1 for container type
## Legend 2 for day type
stacked.bars.problems <- ggplot2::ggplot(data=containers.holidays.collection.days
                                         ,aes(x=date.of.activity
                                              ,y=container.number.adjusted
                                              # Stacks of the bar order, from top to bottom, controlled by the levels
                                              ,fill=factor(container.type, levels = c("PET","cans","glass"))
                                              ,label=container.number.adjusted))+
  # Control transparency of bar color
  ggplot2::geom_col(alpha=0.6)+
  # Draw sum number above the stacked bars using another dataset totals.all.types
  ggplot2::geom_text(data=totals.all.types
                     ,aes(x=date.of.activity, y=total, label=total.label, fill=NULL)
                     ,vjust=-0.2
                     ,size=2.5)+
  # Months on bottom X axis, weeks on top X axis
  ggplot2::scale_x_date(expand = c(0, 0) # expand = c(0,0) to remove margins
                        ,date_breaks = "1 month"
                        ,date_labels = "%b-%Y" # %b Abbreviated month name in current locale (Aug)
                        ,date_minor_breaks = "1 week"
                        # Add a secondary x axis showing week number
                        ,sec.axis = ggplot2::sec_axis(
                          trans= ~ .
                          ,labels = scales::date_format("W%w"))) +
  # Set breaks on Y axis
  ggplot2::scale_y_continuous(breaks = seq(0, 300, 50))+
  ggplot2::labs(title=plot.title.stacked.bars
                ,subtitle = plot.subtitle.stacked.bars
                # Add data source as footnote
                ,caption = caption
                ,x = ""
                ,y = "Number of containers"
                # Change legend title from variable name to text
                ,fill="Container type "
                #,color="Day type"
  )+
  # Remove default theme background color
  ggplot2::theme_bw()+
  ggplot2::theme_minimal()+
  # Apply The Economist theme
  ggthemes::theme_economist_white()+
  ggplot2::theme(plot.title = element_text(hjust = -0.15, vjust=2.12, colour="black", size = 14, face="bold")
                 ,legend.position = "top"
                 ,legend.justification='left'
                 ,legend.direction='horizontal'
                 ,legend.text = element_text(size = 8.5)
                 ,legend.box = "vertical"
                 # Reduce gap between legends
                 ,legend.spacing.y = unit(-0.25, "cm")
                 ,plot.caption = element_text(hjust = 0) # Left align caption
                 ,axis.title = element_text(size = 20)
                 ,axis.text = element_text(size = 15)
                 ,panel.grid.minor = element_blank()
                 ,panel.grid.major = element_line(color = "gray", linewidth = 0.5)
  )+
  ggplot2::geom_point(aes(x=date.of.activity
                          ,y=y.coordinate.holidays.collection.days 
                          ,color=factor(day.type, levels = c("Public holiday", "Recycle collection"))
  )
  ,shape=18 # 15 for solid squares, 18 solid diamonds
  ,size=5
  ,show.legend = TRUE)+
  # Modify legend for aesthetic=fill
  ggplot2::scale_fill_manual(
    # Change legend item color from default to colors
    # Use palette from pals package. as.vector() needed to remove color name
    values=legend.items.color
    ,labels=plot.legend.label.ordered) +
  # Modify legend for aesthetic= color
  ggplot2::scale_color_manual(
    name="Day type"
    ,values = c("Public holiday" = "black","Recycle collection" = "orange")
  )+
  # Setting the order of legends
  ggplot2::guides(fill= guide_legend(order = 1)
                  ,colour=guide_legend(order=2))

# Export plot to a png
base <-300
png(file=file.path(dir.output,"Daily-number-containers-collected-refunded_holidays_plot-has-problems.png")
    ,width=base*8,height=base*6,res=250)
stacked.bars.problems
dev.off()

---

## Stacked bar graph color not matched legend color. New unspecified color appears in bar graph and legend

**data file shared on Google drive**
https://drive.google.com/file/d/14vfxeGN5xjaBA4tCbORzzse26hj0cupZ/view?usp=drive_link

**Color and legend**

#----------
# Color
#----------

# Use a palette with multiple distinct colors
pals::pal.bands(kelly, glasbey, polychrome)
# Only 22 colors are available with 'kelly'.
# Only 32 colors are available with 'glasbey'.
# Only 36 colors are available with 'polychrome'.

# Pick first 8 color from glasbey()
pals::pal.bands(glasbey(n=length(plot.legend.ordered)))

# Display color from color code
colors <- as.vector(pals::glasbey(n=8))
scales::show_col(colors)

# Pair legend item and color
x <- c( Badminton=colors[1]
       ,`Bike Fitting`=colors[2]
       ,Ride=colors[3]
       ,Run=colors[4]
       ,`Strength & Stability workout`=colors[5]
       ,Swim=colors[6]
       ,`Table Tennis`=colors[7]
       ,Walk=colors[8])

scales::show_col(colors)


**problem** activity.type "Strength & Stability Workout" should be in pink as the legend color. But it is in gray bars

# Read tsv into R
activities.2023 <- read.table(
  file = file.path(dir.Strava.output,"Strava-activities-2023.tsv")
  ,sep = "\t"
  ,header = TRUE) |>
  # Change character Dates to date
  dplyr::mutate(start.date.local=as.Date(start.date.local))# dim(activities.2023) 341 3

#-------------
# Legend
#-------------
# Order legend item alphabetically 
plot.legend.ordered <- sort(unique(activities.2023$activity.type)) # length(plot.legend.ordered) 8

ggplot2::ggplot(activities.2023
                ,aes(x=start.date.local
                     ,y=moving.time.hour
                     ,fill = activity.type))+
  ggplot2::geom_bar(position = "stack", stat = "identity") + 
  ggplot2::scale_x_date( 
    limits = as.Date(c('2023-01-01','2023-12-31'))
    ,expand = c(0, 0) # expand = c(0,0) to remove margins
    ,date_breaks = "1 month"
    ,date_minor_breaks = "1 week"
    ,date_labels = "%b" # Abbreviated month name in current locale (Aug)
    # Add a secondary x axis showing week number
    ,sec.axis = ggplot2::sec_axis(
      trans= ~ .
      ,breaks= c(seq.Date(as.Date("2023-01-01"), by="month", length.out = 12)
                 ,"2023-12-25")
      ,labels= scales::date_format("%W"))
  )+
  ggplot2::scale_y_continuous(limits = c(0,8)
                              ,breaks = seq(from=0, to=8, by=1)
                              ,expand = c(0, 0) # expand = c(0,0) to remove margins
  )+
  ggplot2::labs(title="Daily hours spent on physical exercise activity in 2023"
                ,subtitle = "GPS-tracked activities: Ride, Run, Walk"
                ,x = ""
                ,y = "Moving time (h)"
                ,fill="Activity type")+
  # Remove default theme background color
  ggplot2::theme_bw()+
  ggplot2::theme_minimal()+
  # Change bar colors
  ## Use ggplot2::scale_color_manual() to modify aesthetics = "colour"
  ## Use ggplot2::scale_fill_manual() to modify aesthetics = "fill"
  ggplot2::scale_fill_manual(
    # Use palette from pals package. as.vector() needed to remove color name
    values = colors
    ,labels=plot.legend.ordered
    #values=x
    # Reorder legend items from most frequent to least frequent
    # legend text longer than the cutoff is wrapped to multiple lines
    ,limits=stringr::str_wrap(plot.legend.ordered,width=20)
  )

Code above generates this plot


tail(activities.2023,n=3)
#    start.date.local moving.time.hour                activity.type
#339       2023-11-15         2.182778                         Ride
#340       2023-11-15         1.505278 Strength & Stability Workout
#341       2023-11-16         1.158056                          Run

**problem** activity.type "Strength & Stability Workout" shown in grey in legend and graph, not as pink as the color palette

# Pair legend item and color
x <- c( Badminton=colors[1]
       ,`Bike Fitting`=colors[2]
       ,Ride=colors[3]
       ,Run=colors[4]
       ,`Strength & Stability workout`=colors[5]
       ,Swim=colors[6]
       ,`Table Tennis`=colors[7]
       ,Walk=colors[8])

ggplot2::ggplot(activities.2023
                ,aes(x=start.date.local
                     ,y=moving.time.hour
                     ,fill = activity.type))+
  ggplot2::geom_bar(position = "stack", stat = "identity") + 
  ggplot2::scale_x_date( 
    limits = as.Date(c('2023-01-01','2023-12-31'))
    ,expand = c(0, 0) # expand = c(0,0) to remove margins
    ,date_breaks = "1 month"
    ,date_minor_breaks = "1 week"
    ,date_labels = "%b" # Abbreviated month name in current locale (Aug)
    # Add a secondary x axis showing week number
    ,sec.axis = ggplot2::sec_axis(
      trans= ~ .
      ,breaks= c(seq.Date(as.Date("2023-01-01"), by="month", length.out = 12)
                 ,"2023-12-25")
      ,labels= scales::date_format("%W"))
  )+
  ggplot2::scale_y_continuous(limits = c(0,8)
                              ,breaks = seq(from=0, to=8, by=1)
                              ,expand = c(0, 0) # expand = c(0,0) to remove margins
  )+
  ggplot2::labs(title="Daily hours spent on physical exercise activity in 2023"
                ,subtitle = "GPS-tracked activities: Ride, Run, Walk"
                ,x = ""
                ,y = "Moving time (h)"
                ,fill="Activity type")+
  # Remove default theme background color
  ggplot2::theme_bw()+
  ggplot2::theme_minimal()+
  # Change bar colors
  ## Use ggplot2::scale_color_manual() to modify aesthetics = "colour"
  ## Use ggplot2::scale_fill_manual() to modify aesthetics = "fill"
  ggplot2::scale_fill_manual(
    values=x
    # Reorder legend items from most frequent to least frequent
    # legend text longer than the cutoff is wrapped to multiple lines
    ,limits=stringr::str_wrap(plot.legend.ordered,width=20)
  )


---

## Color background of a ggplot2 bar plot
**Problems**
* How to remove these white spaces/margins
* Margin on the left of Jan 2023
* Margin above y=8
* Margin on the right of Jan 2024
* X axis ends at Dec 2023
* Margin below y=0

**plot generated**


**data file shared on Google drive**
https://drive.google.com/file/d/14vfxeGN5xjaBA4tCbORzzse26hj0cupZ/view?usp=drive_link

**Code to produce the plot**

# Read tsv into R
activities.2023 <- read.table(
  file = file.path(dir.Strava.output,"Strava-activities-2023.tsv")
  ,sep = "\t"
  ,header = TRUE) |>
  # Change character Dates to date
  dplyr::mutate(start.date.local=as.Date(start.date.local))# dim(activities.2023) 341 3

# Number of colors needed for activity.type
plot.legend.ordered <- sort(unique(activities.2023$activity.type))
length(plot.legend.ordered) # 8

# Use a palette with >=20 distinct colors
pals::pal.bands(kelly, glasbey, polychrome) 
# Only 22 colors are available with 'kelly'.

# Pick first n colors from kelly(), glasbey()
pals::pal.bands(kelly(n=length(plot.legend.ordered)))

# Manually create start dates and end dates to different time
time.zones <- data.frame(
  date.start=as.Date(c("2023-01-01","2023-01-16","2023-02-06","2023-09-02","2023-10-03"))
  ,date.end=as.Date(c("2023-01-15","2023-02-05","2023-09-01","2023-10-02","2023-12-31"))
  ,time.zone=c("Australia/Brisbane","Asia/Kuala_Lumpur","Australia/Brisbane","Asia/Taipei","Australia/Brisbane")) # dim(time.zones) 5 3

# Pick color red for "Asia/Kuala_Lumpur", darkgreen for "Asia/Taipei", blue for "Australia/Brisbane". Change the color order to meet the legend text order sorted 
time.zones.color <- c("darkred","darkgreen","darkblue")

moving.time.activity.2023 <- ggplot2::ggplot(activities.2023
                                             ,aes(x=start.date.local
                                                  ,y=moving.time.hour
                                                  ,fill = activity.type))+
  ggplot2::geom_bar(position = "stack", stat = "identity") + 
  ggplot2::scale_x_date( 
    limits = as.Date(c('2023-01-01','2023-12-31'))
    ,expand = c(0, 0) # expand = c(0,0) to remove margins
    ,date_breaks = "1 month"
    ,date_minor_breaks = "1 week"
    ,date_labels = "%b" # Abbreviated month name in current locale (Aug)
    # Add a secondary x axis showing week number
    ,sec.axis = dup_axis(name = "",labels = scales::date_format("%W"))
  )+
  ggplot2::scale_y_continuous(limits = c(0,8)
                              ,breaks = seq(from=0, to=8, by=1)
                              ,expand = c(0, 0) # expand = c(0,0) to remove margins
                              )+
  ggplot2::labs(title="Daily hours spent on physical exercise activity in 2023"
                ,subtitle = "GPS-tracked activities: Ride, Run, Walk"
                ,x = ""
                ,y = "Moving time (h)"
                ,fill="Activity type")+
  # Remove default theme background color
  ggplot2::theme_bw()+
  ggplot2::theme_minimal()+
  # Change bar colors
  ## Use ggplot2::scale_color_manual() to modify aesthetics = "colour"
  ## Use ggplot2::scale_fill_manual() to modify aesthetics = "fill"
  ggplot2::scale_fill_manual(
    # Use palette from pals package. as.vector() needed to remove color name
    values = as.vector(pals::kelly(n=8)) # glasbey, polychrome not good looking as kelly
    # Reorder legend items from most frequent to least frequent
    # legend text longer than the cutoff is wrapped to multiple lines
    ,limits=stringr::str_wrap(plot.legend.ordered,width=20)
  )+
  # Create a second fill scale and modify its color
  ggnewscale::new_scale_fill()+
  ggplot2::geom_rect(data=time.zones
                     ,inherit.aes = FALSE
                     ,aes( xmin=date.start
                           ,xmax=date.end
                           ,ymin=0 #ymin=-Inf
                           ,ymax=8 #ymax=Inf
                           ,fill=time.zone)
                     ,alpha=0.15)+
  # Change legend title. Modify color for the fill= aesthetic above
  ggplot2::scale_fill_manual(name="Time Zones",values = time.zones.color)

# Export plot to png
# Create a github-style calender heat-map using ggplot
size.base <- 300
png(file=file.path(dir.Strava.output,"Activity-moving-time-hours-stacked-barplot-background-colored-timezone-2023.png")
    ,width=size.base*8,height=size.base*4.5,res=300)

moving.time.activity.2023

dev.off()

---

## Highlight a range of X axis in a line plot

data file on Google drive
https://drive.google.com/file/d/13B_AfldCOwWXzj_XqUv9249NQHvbsuw2/view?usp=drive_link

B2GC2023 <- readr::read_csv(file = file.path(dir.Strava,"GOTOES_FIT-CSV_4284285070831056.csv")) |>
  dplyr::select(timestamp, position_lat, position_long, altitude, heart_rate, distance, speed, grade, gps_accuracy, calories) |>
  dplyr::mutate(distance.km=distance/1000
  # Set grade >= 15 to NA              
    ,grade.edited=dplyr::case_when(grade < 15 ~ grade, TRUE ~ NA_real_)
  # distance between 8.89 and 108.82km as B2GC, else as non-B2GC
    ,segment=dplyr::case_when(distance.km>=8.89 & distance.km <=108.82 ~ "B2GC", TRUE~ "non-B2GC")
  ) |>
  # Remove speed > max speed in Strava
  dplyr::filter(speed <= 64.2) # dim(B2GC2023) 32883 13

# Create plot titles
plot.title.heartrate <- paste0(
  "Brisbane to Gold Coast 2023 \nSegment B2GC highlighted\n"
  ,"Heart rate (bpm)\n"
  ,"Max rate: ", max(B2GC2023$heart_rate, na.rm = T))

# Heartrate over distance highlighting segment B2GC, distance between 8.89 and 108.82km
plot.heartrate <- ggplot2::ggplot(data=B2GC2023, aes(x=distance.km)) + 
  ggplot2::geom_line(aes(y = heart_rate), color = "darkred")+
  ggplot2::labs(title=plot.title.heartrate)+
  # Change position downwards
  ggplot2::theme(plot.title = element_text(vjust = - 7.5, hjust=0.05, size = 12.5)
                 ,plot.margin = unit(c(0,0.2,0,1), "lines"))+
  gghighlight::gghighlight(distance.km>=8.89 & distance.km<=108.82)+
  ggplot2::ylim(60,200)


---

## Highlight a range of X axis in an area plot

B2GC2023.heartrate <- B2GC2023 |> dplyr::filter(heart_rate>=60 & heart_rate<=200) 

# Area plots with 2 colored areas. Not what I want as there the two groups overlapped
ggplot2::ggplot(data=B2GC2023.heartrate
                ,mapping= aes(x=distance.km, y=heart_rate, group=segment))+
  ggplot2::geom_area(data=subset(B2GC2023.heartrate, segment=="B2GC")
                     ,aes(color=segment, fill=segment)
                     ,alpha=0.5
                     ,position = "identity")+
  ggplot2::geom_area(data=subset(B2GC2023.heartrate, segment=="non-B2GC")
                     ,aes(color=segment, fill=segment)
                     ,alpha=0.2
                     ,position = "identity")+ 
  scale_color_manual(values=c("#FF0000","#000000")) +
  scale_fill_manual(values=c("#FF0000","#000000"))

# Area plots with 2 colored areas. Not what I want as there the two groups overlapped
ggplot2::ggplot(data=B2GC2023.heartrate
                ,aes(x=distance.km, y=heart_rate, fill=segment, alpha=segment))+
  geom_area()+
  scale_fill_manual(values=c("#FF0000", "#000000"))+
  scale_alpha_manual(values= c(1,0.3)) 


B2GC2023.heartrate <- B2GC2023 |> dplyr::filter(heart_rate>=60 & heart_rate<=200) 

# Area plots with 2 colored areas. Not what I want as there the two groups overlapped
ggplot2::ggplot(data=B2GC2023.heartrate
                ,aes(x=distance.km, y=heart_rate, fill=segment, alpha=segment))+
  geom_area()+
  scale_fill_manual(values=c("#FF0000", "#000000"))+
  scale_alpha_manual(values= c(1,0.3)) 


---

## Show number on bottom X axis and dates on top x axis


---

## Arrange multiple ggplot2 plots on one page

### Example with 3 subjects

# Create sample data with 3 subjects for plotting adverse events
subject.017_306 <- data.frame(AESEQ=1
                              ,AETERM="fractured ankle (bilateral)"
                              ,AESTDTC="2021-08-24"
                              ,AESTDY=70
                              ,AEENDTC="2022-11-01"
                              ,AEENDY=504
                              ,SUBJID="017-306") # dim(subject.017_306) 1 7

subject.017_313 <- data.frame(AESEQ=1
                              ,AETERM="blurred vision"
                              ,AESTDTC="2021-09-14"
                              ,AESTDY=29
                              ,AEENDTC="2021-10-05"
                              ,AEENDY=50
                              ,SUBJID="017-313") # dim(subject.017_313) 1 7

subject.023_302 <- data.frame(AESEQ=c(4:1)
                              ,AETERM=c("Tearing", "Grittiness", "eyelid itchiness","Eyelid margin  crusting")
                              ,AESTDTC=c("2022-02-06","2022-02-06","2022-02-06","2022-01-16")
                              ,AESTDY=c(25, 25, 25, 4)
                              ,AEENDTC=c("2022-02-12","2022-03-12","2022-02-12","2022-01-22")
                              ,AEENDY=c(31,59,31,10)
                              ,SUBJID=rep("023-302", 4)
) # dim(subject.023_302) 4 7

# Combine three subjects to one dataframe
sample.data <- rbind(subject.017_306, subject.017_313, subject.023_302) |>
  dplyr::mutate(AETERM=factor(AETERM)
                ,AESTDTC=as.Date(AESTDTC)
                ,AEENDTC=as.Date(AEENDTC)) # dim(sample.data) 6 7

ae.subjects <- unique(sample.data$SUBJID) # length(ae.subjects) 3

# Create an empty list for holding results from the for loop
ggplot.list <- list() # class(ggplot.list) "list" # length(ggplot.list) 0

# Create one plot object per subject
for(i in 1:length(ae.subjects)){
  
  # Get data from 1 subject
  plotdata <- sample.data |> 
  dplyr::filter(SUBJID==ae.subjects[i]) # dim(plotdata) 1 7
  
  # Create plot object name
  plot.object.name <- paste0("plot.", gsub(pattern="-", replacement="_", x=ae.subjects[i]))
  
  # Create 1 plot object per subject
  # Append plot object to the list
  ggplot.list[[i]] <- plotdata %>%
    ggplot2::ggplot(aes(xmin = AESTDTC, xmax = AEENDTC, y = SUBJID)) +
    ggplot2::geom_linerange(aes(color=AETERM)
                            ,linewidth = 5
                            , position = position_dodge(width = 0.5)) +
    ggplot2::scale_x_date(name = ""
                          ,breaks = unique(c(plotdata$AESTDTC, plotdata$AEENDTC))
                          ,sec.axis = dup_axis(
                            labels = unique(c(plotdata$AESTDY, plotdata$AEENDY))
                            ,name = "")
                          )+
    ggplot2::labs(title = paste0("Subject ", ae.subjects[i])
                  ,y=NULL) +
    ggplot2::theme_minimal()+ 
    # Rotate and space bottom x axis label text
    ggplot2::theme(axis.text.x.top = element_text(color = "red")
                   ,axis.text.x.bottom = element_text(angle = 90)
                   ,legend.position= c(0.5, 0.85) 
                   ,legend.direction = "horizontal"
                   # Remove y axis label
                   ,axis.text.y=element_blank()
                   )
  #The end of the loop
}  

# Arrange plots on one page
gridExtra::grid.arrange(ggplot.list, ncol=3, nrow=1) 

The code above produces this plot


### Example with all subjects

References
[ggplot2 - Easy way to mix multiple graphs on the same page](http://www.sthda.com/english/wiki/wiki.php?id_contents=7930)
[Multiple ggplot2 charts on a single page](https://r-graph-gallery.com/261-multiple-graphs-on-same-page.html)
[Lay out multiple ggplot graphs on a page](https://stackoverflow.com/questions/58124284/lay-out-multiple-ggplot-graphs-on-a-page)

# Check the list items
length(ggplot.list) # 27
# Arrange plots on one page using the list
gridExtra::grid.arrange(grobs= ggplot.list[1:9], ncol=3, nrow=3)

which produces


gridExtra::grid.arrange(grobs= ggplot.list[10:18], ncol=3, nrow=3)

which produces


gridExtra::grid.arrange(grobs= ggplot.list[19:27], ncol=3, nrow=3)

which produces


---

## Plot a subject's adverse events as a gantt chart

## Sample data
sample.data <- data.frame(AESEQ=c(4:1)
                          ,AETERM=c("Tearing", "Grittiness", "eyelid itchiness","Eyelid margin  crusting")
                          ,AESTDTC=c("2022-02-06","2022-02-06","2022-02-06","2022-01-16")
                          ,AESTDY=c(25, 25, 25, 4)
                          ,AEENDTC=c("2022-02-12","2022-03-12","2022-02-12","2022-01-22")
                          ,AEENDY=c(31,59,31,10)
                          ,SUBJID=rep("023-302", 4)
                          )

SUBJID <- unique(sample.data$SUBJID)

sample.data %>%
  ggplot2::ggplot(aes(xmin = AESTDTC, xmax = AEENDTC, y = SUBJID, color = AETERM)
                  ,show.legend = TRUE) +
  ggplot2::geom_linerange(linewidth = 5, position = position_dodge(width = 0.5)
                          ,show.legend = TRUE) +
  ggplot2::labs(title = paste0("Adverse events of subject ", SUBJID)
                ,x = "Start and end dates"
                ,y="") +
  ggplot2::theme_minimal(base_size = 16)+ 
  # Rotate and space bottom x axis label text
  ggplot2::theme(axis.text.x = element_text(angle = 0, vjust = 0.5, hjust=1)
                 # Remove y axis label
                 ,axis.text.y=element_blank()
        # Legend position: top right inside plot
        ## The coordinates for legend.position are x- and y- offsets from the bottom-left of the plot, ranging from 0 - 1.
                ,legend.position = c(0.75,0.8))

---

The produced figure:


---

The desired figure:


---