Is there an R function to dodge overlapping values in a geom_segment plot?

Question

I have this data:

"","NAME","PRE","start","end","jit"
"1","A","Treatment A",2024,2024.5,0
"2","B","Treatment A",2026,2026.5,0
"3","C","Treatment A",2024,2024.5,0
"4","D","Treatment A",2026,2026.5,0
"5","E","Treatment A",2026,2026.5,0
"6","F","Treatment A",2027,2027.5,0
"7","G","Treatment A",2024,2024.5,0
"8","H","Treatment A",2027,2027.5,0
"9","I","Treatment A",2024,2024.5,0
"10","J","Treatment A",2025,2025.5,0
"11","K","Treatment A",2027,2027.5,0
"12","L","Treatment A",2024,2024.5,0
"13","M","Treatment A",2027,2027.5,0
"14","N","Treatment A",2026,2026.5,0
"15","O","Treatment A",2025,2025.5,0
"16","P","Treatment A",2024,2024.5,0
"17","Q","Treatment A",2027,2027.5,0
"18","R","Treatment A",2024,2024.5,0
"19","S","Treatment A",2025,2025.5,0
"20","T","Treatment A",2025,2025.5,0
"21","U","Treatment A",2025,2025.5,0
"22","V","Treatment A",2024,2024.5,0
"23","W","Treatment A",2026,2026.5,0
"24","X","Treatment A",2025,2025.5,0
"25","Y","Treatment A",2027,2027.5,0
"26","Z","Treatment A",2025,2025.5,0
"27","AA","Treatment A",2025,2025.5,0
"28","AB","Treatment A",2024,2024.5,0
"29","AC","Treatment A",2027,2027.5,0
"30","AD","Treatment A",2026,2026.5,0
"31","AE","Treatment A",2027,2027.5,0
"32","AF","Treatment A",2026,2026.5,0
"33","AG","Treatment A",2025,2025.5,0
"34","AH","Treatment A",2027,2027.5,0
"35","AI","Treatment A",2025,2025.5,0
"36","AJ","Treatment A",2026,2026.5,0
"37","AK","Treatment A",2026,2026.5,0
"38","A","Treatment F",2028,2028.5,0
"39","B","Treatment F",2027,2027.5,0
"40","C","Treatment F",2030,2030.5,0
"41","D","Treatment F",2032,2032.5,0
"42","E","Treatment F",2027,2027.5,0
"43","F","Treatment F",NA,NA,0
"44","G","Treatment F",2031,2031.5,0
"45","H","Treatment F",NA,NA,0
"46","I","Treatment F",2032,2032.5,0
"47","J","Treatment F",2026,2026.5,0
"48","K","Treatment F",2028,2028.5,0
"49","L","Treatment F",2031,2031.5,0
"50","M","Treatment F",NA,NA,0
"51","N","Treatment F",2027,2027.5,0
"52","O","Treatment F",2026,2026.5,0
"53","P","Treatment F",2025,2025.5,0
"54","Q","Treatment F",2028,2028.5,0
"55","R","Treatment F",2025,2025.5,0
"56","S","Treatment F",2026,2026.5,0
"57","T","Treatment F",2026,2026.5,0
"58","U","Treatment F",2026,2026.5,0
"59","V","Treatment F",2025,2025.5,0
"60","W","Treatment F",2027,2027.5,0
"61","X","Treatment F",2033,2033.5,0
"62","Y","Treatment F",2033,2033.5,0
"63","Z","Treatment F",2030,2030.5,0
"64","AA","Treatment F",2026,2026.5,0
"65","AB","Treatment F",2031,2031.5,0
"66","AC","Treatment F",2033,2033.5,0
"67","AD","Treatment F",2031,2031.5,0
"68","AE","Treatment F",2028,2028.5,0
"69","AF","Treatment F",NA,NA,0
"70","AG","Treatment F",2031,2031.5,0
"71","AH","Treatment F",2028,2028.5,0
"72","AI","Treatment F",2030,2030.5,0
"73","AJ","Treatment F",2031,2031.5,0
"74","AK","Treatment F",2027,2027.5,0
"75","A","Treatment I",2030,2030.5,0
"76","B","Treatment I",2029,2029.5,0
"77","C","Treatment I",2032,2032.5,0
"78","D","Treatment I",2034,2034.5,0
"79","E","Treatment I",2029,2029.5,0
"80","F","Treatment I",NA,NA,0
"81","G","Treatment I",2033,2033.5,0
"82","H","Treatment I",NA,NA,0
"83","I","Treatment I",2034,2034.5,0
"84","J","Treatment I",2028,2028.5,0
"85","K","Treatment I",2030,2030.5,0
"86","L","Treatment I",2033,2033.5,0
"87","M","Treatment I",NA,NA,0
"88","N","Treatment I",2029,2029.5,0
"89","O","Treatment I",2028,2028.5,0
"90","P","Treatment I",2027,2027.5,0
"91","Q","Treatment I",2030,2030.5,0
"92","R","Treatment I",2027,2027.5,0
"93","S","Treatment I",2028,2028.5,0
"94","T","Treatment I",2028,2028.5,0
"95","U","Treatment I",2028,2028.5,0
"96","V","Treatment I",2027,2027.5,0
"97","W","Treatment I",2029,2029.5,0
"98","X","Treatment I",2035,2035.5,0
"99","Y","Treatment I",2035,2035.5,0
"100","Z","Treatment I",2032,2032.5,0
"101","AA","Treatment I",2028,2028.5,0
"102","AB","Treatment I",2033,2033.5,0
"103","AC","Treatment I",2035,2035.5,0
"104","AD","Treatment I",2033,2033.5,0
"105","AE","Treatment I",2030,2030.5,0
"106","AF","Treatment I",NA,NA,0
"107","AG","Treatment I",2033,2033.5,0
"108","AH","Treatment I",2030,2030.5,0
"109","AI","Treatment I",2032,2032.5,0
"110","AJ","Treatment I",2033,2033.5,0
"111","AK","Treatment I",2029,2029.5,0
"112","A","Treatment B",2028,2028.5,0
"113","B","Treatment B",2028,2028.5,0
"114","C","Treatment B",2028,2028.5,0
"115","D","Treatment B",2028,2028.5,0
"116","E","Treatment B",2029,2029.5,0
"117","F","Treatment B",2028,2028.5,0
"118","G","Treatment B",2028,2028.5,0
"119","H","Treatment B",2029,2029.5,0
"120","I","Treatment B",2029,2029.5,0
"121","J","Treatment B",2030,2030.5,0
"122","K","Treatment B",2030,2030.5,0
"123","L","Treatment B",2029,2029.5,0
"124","M","Treatment B",2030,2030.5,0
"125","N","Treatment B",2030,2030.5,0
"126","O","Treatment B",2030,2030.5,0
"127","P","Treatment B",2030,2030.5,0
"128","Q","Treatment B",2029,2029.5,0
"129","R","Treatment B",2029,2029.5,0
"130","S","Treatment B",2031,2031.5,0
"131","T","Treatment B",2031,2031.5,0
"132","U","Treatment B",2031,2031.5,0
"133","V","Treatment B",2030,2030.5,0
"134","W","Treatment B",2031,2031.5,0
"135","X","Treatment B",2031,2031.5,0
"136","Y","Treatment B",2032,2032.5,0
"137","Z","Treatment B",2032,2032.5,0
"138","AA","Treatment B",2031,2031.5,0
"139","AB","Treatment B",2032,2032.5,0
"140","AC","Treatment B",2032,2032.5,0
"141","AD","Treatment B",2033,2033.5,0
"142","AE","Treatment B",2033,2033.5,0
"143","AF","Treatment B",2033,2033.5,0
"144","AG","Treatment B",2033,2033.5,0
"145","AH","Treatment B",2033,2033.5,0
"146","AI","Treatment B",2033,2033.5,0
"147","AJ","Treatment B",2032,2032.5,0
"148","AK","Treatment B",2032,2032.5,0
"149","A","Treatment D",NA,NA,0
"150","B","Treatment D",NA,NA,0
"151","C","Treatment D",NA,NA,0
"152","D","Treatment D",NA,NA,0
"153","E","Treatment D",NA,NA,0
"154","F","Treatment D",NA,NA,0
"155","G","Treatment D",NA,NA,0
"156","H","Treatment D",NA,NA,0
"157","I","Treatment D",NA,NA,0
"158","J","Treatment D",NA,NA,0
"159","K","Treatment D",NA,NA,0
"160","L","Treatment D",NA,NA,0
"161","M","Treatment D",NA,NA,0
"162","N","Treatment D",NA,NA,0
"163","O","Treatment D",NA,NA,0
"164","P","Treatment D",NA,NA,0
"165","Q","Treatment D",NA,NA,0
"166","R","Treatment D",NA,NA,0
"167","S","Treatment D",NA,NA,0
"168","T","Treatment D",NA,NA,0
"169","U","Treatment D",NA,NA,0
"170","V","Treatment D",NA,NA,0
"171","W","Treatment D",NA,NA,0
"172","X","Treatment D",NA,NA,0
"173","Y","Treatment D",NA,NA,0
"174","Z","Treatment D",NA,NA,0
"175","AA","Treatment D",NA,NA,0
"176","AB","Treatment D",NA,NA,0
"177","AC","Treatment D",NA,NA,0
"178","AD","Treatment D",NA,NA,0
"179","AE","Treatment D",NA,NA,0
"180","AF","Treatment D",NA,NA,0
"181","AG","Treatment D",NA,NA,0
"182","AH","Treatment D",NA,NA,0
"183","AI","Treatment D",NA,NA,0
"184","AJ","Treatment D",NA,NA,0
"185","AK","Treatment D",NA,NA,0
"186","A","Treatment E",NA,NA,0
"187","B","Treatment E",NA,NA,0
"188","C","Treatment E",NA,NA,0
"189","D","Treatment E",NA,NA,0
"190","E","Treatment E",NA,NA,0
"191","F","Treatment E",NA,NA,0
"192","G","Treatment E",NA,NA,0
"193","H","Treatment E",NA,NA,0
"194","I","Treatment E",NA,NA,0
"195","J","Treatment E",NA,NA,0
"196","K","Treatment E",NA,NA,0
"197","L","Treatment E",NA,NA,0
"198","M","Treatment E",NA,NA,0
"199","N","Treatment E",NA,NA,0
"200","O","Treatment E",NA,NA,0
"201","P","Treatment E",NA,NA,0
"202","Q","Treatment E",NA,NA,0
"203","R","Treatment E",NA,NA,0
"204","S","Treatment E",NA,NA,0
"205","T","Treatment E",NA,NA,0
"206","U","Treatment E",NA,NA,0
"207","V","Treatment E",NA,NA,0
"208","W","Treatment E",NA,NA,0
"209","X","Treatment E",NA,NA,0
"210","Y","Treatment E",NA,NA,0
"211","Z","Treatment E",NA,NA,0
"212","AA","Treatment E",NA,NA,0
"213","AB","Treatment E",NA,NA,0
"214","AC","Treatment E",NA,NA,0
"215","AD","Treatment E",NA,NA,0
"216","AE","Treatment E",NA,NA,0
"217","AF","Treatment E",NA,NA,0
"218","AG","Treatment E",NA,NA,0
"219","AH","Treatment E",NA,NA,0
"220","AI","Treatment E",NA,NA,0
"221","AJ","Treatment E",NA,NA,0
"222","AK","Treatment E",NA,NA,0
"223","A","Treatment C",2028.5,2029,0
"224","B","Treatment C",2028.5,2029,0
"225","C","Treatment C",2028.5,2029,0
"226","D","Treatment C",2028.5,2029,0
"227","E","Treatment C",2029.5,2030,0
"228","F","Treatment C",2028.5,2029,0
"229","G","Treatment C",2028.5,2029,0
"230","H","Treatment C",2029.5,2030,0
"231","I","Treatment C",2029.5,2030,0
"232","J","Treatment C",2030.5,2031,0
"233","K","Treatment C",2030.5,2031,0
"234","L","Treatment C",2029.5,2030,0
"235","M","Treatment C",2030.5,2031,0
"236","N","Treatment C",2030.5,2031,0
"237","O","Treatment C",2030.5,2031,0
"238","P","Treatment C",2030.5,2031,0
"239","Q","Treatment C",2029.5,2030,0
"240","R","Treatment C",2029.5,2030,0
"241","S","Treatment C",2031.5,2032,0
"242","T","Treatment C",2031.5,2032,0
"243","U","Treatment C",2031.5,2032,0
"244","V","Treatment C",2030.5,2031,0
"245","W","Treatment C",2031.5,2032,0
"246","X","Treatment C",2031.5,2032,0
"247","Y","Treatment C",2032.5,2033,0
"248","Z","Treatment C",2032.5,2033,0
"249","AA","Treatment C",2031.5,2032,0
"250","AB","Treatment C",2032.5,2033,0
"251","AC","Treatment C",2032.5,2033,0
"252","AD","Treatment C",2033.5,2034,0
"253","AE","Treatment C",2033.5,2034,0
"254","AF","Treatment C",2033.5,2034,0
"255","AG","Treatment C",2033.5,2034,0
"256","AH","Treatment C",2033.5,2034,0
"257","AI","Treatment C",2033.5,2034,0
"258","AJ","Treatment C",2032.5,2033,0
"259","AK","Treatment C",2032.5,2033,0
"260","A","Treatment G",2028.5,2029,0
"261","B","Treatment G",2027.5,2028,0
"262","C","Treatment G",2030.5,2031,0
"263","D","Treatment G",2032.5,2033,0
"264","E","Treatment G",2027.5,2028,0
"265","F","Treatment G",NA,NA,0
"266","G","Treatment G",2031.5,2032,0
"267","H","Treatment G",NA,NA,0
"268","I","Treatment G",2032.5,2033,0
"269","J","Treatment G",2026.5,2027,0
"270","K","Treatment G",2028.5,2029,0
"271","L","Treatment G",2031.5,2032,0
"272","M","Treatment G",NA,NA,0
"273","N","Treatment G",2027.5,2028,0
"274","O","Treatment G",2026.5,2027,0
"275","P","Treatment G",2025.5,2026,0
"276","Q","Treatment G",2028.5,2029,0
"277","R","Treatment G",2025.5,2026,0
"278","S","Treatment G",2026.5,2027,0
"279","T","Treatment G",2026.5,2027,0
"280","U","Treatment G",2026.5,2027,0
"281","V","Treatment G",2025.5,2026,0
"282","W","Treatment G",2027.5,2028,0
"283","X","Treatment G",2033.5,2034,0
"284","Y","Treatment G",2033.5,2034,0
"285","Z","Treatment G",2030.5,2031,0
"286","AA","Treatment G",2026.5,2027,0
"287","AB","Treatment G",2031.5,2032,0
"288","AC","Treatment G",2033.5,2034,0
"289","AD","Treatment G",2031.5,2032,0
"290","AE","Treatment G",2028.5,2029,0
"291","AF","Treatment G",NA,NA,0
"292","AG","Treatment G",2031.5,2032,0
"293","AH","Treatment G",2028.5,2029,0
"294","AI","Treatment G",2030.5,2031,0
"295","AJ","Treatment G",2031.5,2032,0
"296","AK","Treatment G",2027.5,2028,0
"297","A","Treatment H",2029,2029.5,0
"298","B","Treatment H",2028,2028.5,0
"299","C","Treatment H",2031,2031.5,0
"300","D","Treatment H",2033,2033.5,0
"301","E","Treatment H",2028,2028.5,0
"302","F","Treatment H",NA,NA,0
"303","G","Treatment H",2032,2032.5,0
"304","H","Treatment H",NA,NA,0
"305","I","Treatment H",2033,2033.5,0
"306","J","Treatment H",2027,2027.5,0
"307","K","Treatment H",2029,2029.5,0
"308","L","Treatment H",2032,2032.5,0
"309","M","Treatment H",NA,NA,0
"310","N","Treatment H",2028,2028.5,0
"311","O","Treatment H",2027,2027.5,0
"312","P","Treatment H",2026,2026.5,0
"313","Q","Treatment H",2029,2029.5,0
"314","R","Treatment H",2026,2026.5,0
"315","S","Treatment H",2027,2027.5,0
"316","T","Treatment H",2027,2027.5,0
"317","U","Treatment H",2027,2027.5,0
"318","V","Treatment H",2026,2026.5,0
"319","W","Treatment H",2028,2028.5,0
"320","X","Treatment H",2034,2034.5,0
"321","Y","Treatment H",2034,2034.5,0
"322","Z","Treatment H",2031,2031.5,0
"323","AA","Treatment H",2027,2027.5,0
"324","AB","Treatment H",2032,2032.5,0
"325","AC","Treatment H",2034,2034.5,0
"326","AD","Treatment H",2032,2032.5,0
"327","AE","Treatment H",2029,2029.5,0
"328","AF","Treatment H",NA,NA,0
"329","AG","Treatment H",2032,2032.5,0
"330","AH","Treatment H",2029,2029.5,0
"331","AI","Treatment H",2031,2031.5,0
"332","AJ","Treatment H",2032,2032.5,0
"333","AK","Treatment H",2028,2028.5,0
"334","A","Treatment I",2031,2031.5,0
"335","A","Treatment I",2032,2032.5,0
"336","A","Treatment I",2033,2033.5,0
"337","B","Treatment I",2030,2030.5,0
"338","B","Treatment I",2031,2031.5,0
"339","B","Treatment I",2032,2032.5,0
"340","C","Treatment I",2033,2033.5,0
"341","C","Treatment I",2034,2034.5,0
"342","C","Treatment I",2035,2035.5,0
"343","D","Treatment I",2035,2035.5,0
"344","D","Treatment I",2036,2036.5,0
"345","D","Treatment I",2037,2037.5,0
"346","E","Treatment I",2030,2030.5,0
"347","E","Treatment I",2031,2031.5,0
"348","E","Treatment I",2032,2032.5,0
"349","F","Treatment I",NA,NA,0
"350","F","Treatment I",NA,NA,0
"351","F","Treatment I",NA,NA,0
"352","G","Treatment I",2034,2034.5,0
"353","G","Treatment I",2035,2035.5,0
"354","G","Treatment I",2036,2036.5,0
"355","H","Treatment I",NA,NA,0
"356","H","Treatment I",NA,NA,0
"357","H","Treatment I",NA,NA,0
"358","I","Treatment I",2035,2035.5,0
"359","I","Treatment I",2036,2036.5,0
"360","I","Treatment I",2037,2037.5,0
"361","K","Treatment I",2031,2031.5,0
"362","K","Treatment I",2032,2032.5,0
"363","K","Treatment I",2033,2033.5,0
"364","L","Treatment I",2034,2034.5,0
"365","L","Treatment I",2035,2035.5,0
"366","L","Treatment I",2036,2036.5,0
"367","M","Treatment I",NA,NA,0
"368","M","Treatment I",NA,NA,0
"369","M","Treatment I",NA,NA,0
"370","N","Treatment I",2030,2030.5,0
"371","N","Treatment I",2031,2031.5,0
"372","N","Treatment I",2032,2032.5,0
"373","O","Treatment I",2029,2029.5,0
"374","O","Treatment I",2030,2030.5,0
"375","O","Treatment I",2031,2031.5,0
"376","P","Treatment I",2028,2028.5,0
"377","P","Treatment I",2029,2029.5,0
"378","P","Treatment I",2030,2030.5,0
"379","Q","Treatment I",2031,2031.5,0
"380","Q","Treatment I",2032,2032.5,0
"381","Q","Treatment I",2033,2033.5,0
"382","R","Treatment I",2028,2028.5,0
"383","R","Treatment I",2029,2029.5,0
"384","R","Treatment I",2030,2030.5,0
"385","V","Treatment I",2028,2028.5,0
"386","V","Treatment I",2029,2029.5,0
"387","V","Treatment I",2030,2030.5,0
"388","W","Treatment I",2030,2030.5,0
"389","W","Treatment I",2031,2031.5,0
"390","W","Treatment I",2032,2032.5,0
"391","X","Treatment I",2036,2036.5,0
"392","X","Treatment I",2037,2037.5,0
"393","X","Treatment I",2038,2038.5,0
"394","Y","Treatment I",2036,2036.5,0
"395","Y","Treatment I",2037,2037.5,0
"396","Y","Treatment I",2038,2038.5,0
"397","Z","Treatment I",2033,2033.5,0
"398","Z","Treatment I",2034,2034.5,0
"399","Z","Treatment I",2035,2035.5,0
"400","AA","Treatment I",2029,2029.5,0
"401","AA","Treatment I",2030,2030.5,0
"402","AA","Treatment I",2031,2031.5,0
"403","AB","Treatment I",2034,2034.5,0
"404","AB","Treatment I",2035,2035.5,0
"405","AB","Treatment I",2036,2036.5,0
"406","AC","Treatment I",2036,2036.5,0
"407","AC","Treatment I",2037,2037.5,0
"408","AC","Treatment I",2038,2038.5,0
"409","AD","Treatment I",2034,2034.5,0
"410","AD","Treatment I",2035,2035.5,0
"411","AD","Treatment I",2036,2036.5,0
"412","AE","Treatment I",2031,2031.5,0
"413","AE","Treatment I",2032,2032.5,0
"414","AE","Treatment I",2033,2033.5,0
"415","AF","Treatment I",NA,NA,0
"416","AF","Treatment I",NA,NA,0
"417","AF","Treatment I",NA,NA,0
"418","AG","Treatment I",2034,2034.5,0
"419","AG","Treatment I",2035,2035.5,0
"420","AG","Treatment I",2036,2036.5,0
"421","AH","Treatment I",2031,2031.5,0
"422","AH","Treatment I",2032,2032.5,0
"423","AH","Treatment I",2033,2033.5,0
"424","AI","Treatment I",2033,2033.5,0
"425","AI","Treatment I",2034,2034.5,0
"426","AI","Treatment I",2035,2035.5,0
"427","AJ","Treatment I",2034,2034.5,0
"428","AJ","Treatment I",2035,2035.5,0
"429","AJ","Treatment I",2036,2036.5,0
"430","AK","Treatment I",2030,2030.5,0
"431","AK","Treatment I",2031,2031.5,0
"432","AK","Treatment I",2032,2032.5,0

And this code:

 plot <- ggplot(df, aes(x=start, xend=end, y=NAME, 
                                         yend=NAME, color=PRE)) +
  geom_segment(size = 2, lineend = "round") +
  scale_y_discrete(limits=rev) +
  xlim(2023,2044) +
  theme(panel.background = element_rect(fill = 'white', color = 'white'),
        panel.grid.major.y = element_line(colour = "grey", 
                                        linetype = "solid", 
                                        linewidth = 0.1),
        panel.grid.major.x = element_line(colour = "grey", 
                                          linetype = "dashed", 
                                          linewidth = 0.05),
        legend.position = "right", legend.justification = "top",
        legend.text = element_text(size = 6),
        legend.title = element_text(size = 10, face = "bold"),
        axis.text=element_text(size = 6),
        axis.title = element_text(size = 10, face = "bold", margin = margin(t = 10)),
        plot.title = element_text(size = 14, face = "bold")) +
  guides(col = guide_legend(ncol = 1,
                            title.position = "top",
                            keyheight = 0.3,
                            keywidth = 0.6))

Currently yielding this result:

As you can see, there are instances where a common start date between prescriptions creates an overlap where you can only see one of the prescriptions. This happens frequently.

Is there an eloquent way to utilize a dodge or jitter (or similar) in a geom_segment() plot so that in instances where there is more than one prescription on the same start, they offset, revealing both. The possibility of having three aligning prescriptions on the same start is somewhat remote, but not impossible, so ideally the solution would scale so that should that issue arise, it would address that as well.

Just to be clear, you only want to dodge the overlapping segments when they overlap. Otherwise, if the segments do not overlap for a particular observation, you want to leave them untouched? — DaveArmstrong, Aug 14 '23 at 02:08

Allan Cameron · Accepted Answer · 2023-08-14T17:09:35.427

The main challenge is counting the number of simultaneous prescriptions per individual and converting this into a grouping variable which you can use for dodging via position_nudge

To do this properly, you will probably need to find all co-occurring prescriptions within each group as an adjacency matrix and get the connected components of the implied graph. This isn't trivial.

plot_df <- df %>%
  filter(!is.na(start)) %>%
  split(.$NAME) %>%
  lapply(function(x) {
    d <- within(x, instance <- seq(nrow(x)))
  
    groups <- outer(seq(nrow(d)), seq(nrow(d)), function(i, j) {
      (d$start[i] <= d$start[j] & d$end[i] >= d$start[j]) |
        (d$start[j] <= d$start[i] & d$end[j] >= d$start[i]) 
    }) |> igraph::graph_from_adjacency_matrix() |>
      igraph::components()
    
    d$group <- groups$membership
    d %>%
      group_by(group) %>%
      mutate(pos = row_number()) %>%
      mutate(pos = (pos - mean(pos))/8)
  }) %>%
  bind_rows()

The thickness of your lines and large number of individuals on the plot doesn't leave much room for dodging, so the final plot loses some of its charm and is quite confusing to look at.

ggplot(plot_df, aes(y = NAME, xmin = start, xmax = end, colour = PRE, 
             group = dodge_group)) +
  geom_linerange(position = position_nudge(y = plot_df$dodge_group), 
                 linewidth = 1,
                 lineend = 'round', key_glyph = draw_key_path) +
  scale_y_discrete(limits = rev) +
  xlim(2023, 2044) +
  theme_minimal()

If you limit the number of entries on the y axis to say, 12 individuals, this isn't as much of a problem:

ggplot(plot_df %>% filter(NAME %in% LETTERS[1:12]),
       aes(y = NAME, xmin = start, xmax = end, colour = PRE)) +
  geom_linerange(position = position_nudge(
    y = plot_df %>% filter(NAME %in% LETTERS[1:12]) %>% pull(pos)),
    linewidth = 2,
    lineend = 'round', key_glyph = draw_key_path) +
  scale_y_discrete(limits = rev) +
  xlim(2023, 2044) +
  theme_minimal()

Thanks! It's close. Beggars can't be choosers, but I'll ask; it seems like the dodge logic is unnecessarily being applied in several cases. Originally I thought the dodge might be being set standard across treatment levels, but at looking at the data, this isn't true. Any feeling as to what's going on with, say treatment G, H, or C for example? Those seem to be dodging across all levels? I seems to have done it once or twice as well. — UnsoughtNine, Aug 14 '23 at 16:01
@UnsoughtNine I don't think that's the case. Look at the second plot. Treatment I is dodged for patient B and E, but not in the others when there are no co-prescriptions. The doding only happens when there is more than one PRE per NAME at the same time - that's specifically what the code does. — Allan Cameron, Aug 14 '23 at 16:01
You're correct. It is not dodging by level. For everyone else's sake: I had re-written an earlier comment at the same time as Allan responded to it. I had suggested the logic might be dodging by treatment level, it is not doing that. That said, I guess my question is for treatment C, for example, why has it dodged in all cases? Under NAME level E, C is actually hidden behind I based on the data. — UnsoughtNine, Aug 14 '23 at 16:10
@UnsoughtNine hm, I see what you mean. It's because with this method every PRE is dodged to the position of the maximum co-occurring PRE values. This means if there are two separate PRE segments that are 'bridged' by a third, the rightmost segment will dodged to the same position as the bridging segment. We might actually need graph grouping to fix that. — Allan Cameron, Aug 14 '23 at 16:23

Is there an R function to dodge overlapping values in a geom_segment plot?

1 Answers1