How to avoid overlapp in geom_line
I have a really long and extended code, which I have created with graphs that shows lines overlapping.
Could you please suggest something to disentangle this and make the reproduction clearer? Maybe some other options to modify the size of graph itself?
For example when save graphs with ggsave.
Thanks
REPREX
Here the datset I am working on
df = structure(list(ANT = c("MEDIUM", "MEDIUM", "MEDIUM", "LOW", "LOW",
"LOW", "HIGH", "HIGH", "HIGH"), BUT = c("flat", "tighted", "curved",
"flat", "tighted", "curved", "flat", "tighted", "curved"), var = c("sighted",
"sighted", "sighted", "sighted", "sighted", "sighted", "sighted",
"sighted", "sighted"), mean = c(24.9795700007983, 22.5476640156841,
24.4568444611505, 24.4608952261011, 22.179843452558, 25.1211893108135,
24.1807279709165, 21.9700173259632, 25.5690587972475), low = c(24.1929993862564,
22.0173613402898, 23.7793134256169, 23.5748441551253, 21.2709153846706,
24.2111126105412, 23.376952383782, 21.3272260871708, 24.7053231240633
), up = c(25.7661406153403, 23.0779666910784, 25.1343754966842,
25.3469462970768, 23.0887715204454, 26.0312660110858, 24.984503558051,
22.6128085647556, 26.4327944704316)), row.names = c(NA, -9L), class = c("tbl_df",
"tbl", "data.frame"))
the table where to get the statistics label from
val = structure(list(group1 = c("flat", "flat", "tighted", "flat",
"flat", "tighted", "flat", "flat", "tighted"), group2 = c("tighted",
"curved", "curved", "tighted", "curved", "curved", "tighted",
"curved", "curved"), y.position = c(45.985, 48.4375, 50.89, 53.985,
56.4375, 58.89, 58.493, 60.9455, 63.398), lab = c("0.0132 - *",
"0.585 - ns", "0.0494 - ns", "0.0826 - ns", "0.618 - ns",
"0.0214 - ns", "0.0458 - ns", "0.211 - ns", "0.00171 - **"
)), row.names = c(NA, -9L), class = c("tbl_df", "tbl", "data.frame"
))
and the code that I have used
library(ggplot2)
library(ggpubr)
ggplot(df,
aes(x= BUT, y= mean,
colour= ANT, group = ANT)) +
geom_errorbar(aes(ymin= low,
ymax= up),
colour="black", width=.10) +
geom_line() +
geom_point(size= 3, shape= 21, fill="white") +
stat_pvalue_manual(
val,
step.increase=0.05,label = "lab")
Solution
This is not how I would approach the problem - I would exclude non-significant interactions from the plot to 'tidy' things up - but here is an answer to your question:
library(tidyverse)
library(ggpubr)
df = structure(list(ANT = c("MEDIUM", "MEDIUM", "MEDIUM", "LOW", "LOW",
"LOW", "HIGH", "HIGH", "HIGH"), BUT = c("flat", "tighted", "curved",
"flat", "tighted", "curved", "flat", "tighted", "curved"), var = c("sighted",
"sighted", "sighted", "sighted", "sighted", "sighted", "sighted",
"sighted", "sighted"), mean = c(24.9795700007983, 22.5476640156841,
24.4568444611505, 24.4608952261011, 22.179843452558, 25.1211893108135,
24.1807279709165, 21.9700173259632, 25.5690587972475), low = c(24.1929993862564,
22.0173613402898, 23.7793134256169, 23.5748441551253, 21.2709153846706,
24.2111126105412, 23.376952383782, 21.3272260871708, 24.7053231240633
), up = c(25.7661406153403, 23.0779666910784, 25.1343754966842,
25.3469462970768, 23.0887715204454, 26.0312660110858, 24.984503558051,
22.6128085647556, 26.4327944704316)), row.names = c(NA, -9L), class = c("tbl_df",
"tbl", "data.frame"))
val = structure(list(group1 = c("flat", "flat", "tighted", "flat",
"flat", "tighted", "flat", "flat", "tighted"), group2 = c("tighted",
"curved", "curved", "tighted", "curved", "curved", "tighted",
"curved", "curved"), y.position = c(45.985, 48.4375, 50.89, 53.985,
56.4375, 58.89, 58.493, 60.9455, 63.398), lab = c("0.0132 - *",
"0.585 - ns", "0.0494 - ns", "0.0826 - ns", "0.618 - ns",
"0.0214 - ns", "0.0458 - ns", "0.211 - ns", "0.00171 - **"
)), row.names = c(NA, -9L), class = c("tbl_df", "tbl", "data.frame"
))
val <- val %>%
mutate(lab = paste0(group1, " vs ", group2, ": ", lab))
ggplot(df,
aes(x= BUT, y= mean,
colour= ANT, group = ANT)) +
geom_errorbar(aes(ymin= low,
ymax= up),
colour="black", width=.10) +
geom_line() +
geom_point(size= 3, shape= 21, fill="white") +
stat_pvalue_manual(val, step.increase=0.075,
label = "lab", size = 2.5,
y.position = 27)
Created on 2023-04-28 with reprex v2.0.2
If you wanted to only plot the significant terms on the plot, you could do something like:
library(tidyverse)
library(ggpubr)
df = structure(list(ANT = c("MEDIUM", "MEDIUM", "MEDIUM", "LOW", "LOW",
"LOW", "HIGH", "HIGH", "HIGH"), BUT = c("flat", "tighted", "curved",
"flat", "tighted", "curved", "flat", "tighted", "curved"), var = c("sighted",
"sighted", "sighted", "sighted", "sighted", "sighted", "sighted",
"sighted", "sighted"), mean = c(24.9795700007983, 22.5476640156841,
24.4568444611505, 24.4608952261011, 22.179843452558, 25.1211893108135,
24.1807279709165, 21.9700173259632, 25.5690587972475), low = c(24.1929993862564,
22.0173613402898, 23.7793134256169, 23.5748441551253, 21.2709153846706,
24.2111126105412, 23.376952383782, 21.3272260871708, 24.7053231240633
), up = c(25.7661406153403, 23.0779666910784, 25.1343754966842,
25.3469462970768, 23.0887715204454, 26.0312660110858, 24.984503558051,
22.6128085647556, 26.4327944704316)), row.names = c(NA, -9L), class = c("tbl_df",
"tbl", "data.frame"))
val = structure(list(group1 = c("flat", "flat", "tighted", "flat",
"flat", "tighted", "flat", "flat", "tighted"), group2 = c("tighted",
"curved", "curved", "tighted", "curved", "curved", "tighted",
"curved", "curved"), y.position = c(45.985, 48.4375, 50.89, 53.985,
56.4375, 58.89, 58.493, 60.9455, 63.398), lab = c("0.0132 - *",
"0.585 - ns", "0.0494 - ns", "0.0826 - ns", "0.618 - ns",
"0.0214 - ns", "0.0458 - ns", "0.211 - ns", "0.00171 - **"
)), row.names = c(NA, -9L), class = c("tbl_df", "tbl", "data.frame"
))
val <- val %>%
mutate(lab = paste0(group1, " vs ", group2, ": p=", lab)) %>%
filter(str_detect(lab, "ns", negate = TRUE))
jitter_seed <- 123
ggplot(df,
aes(x = BUT, y = mean,
colour = ANT, group = ANT)) +
geom_errorbar(aes(ymin = low,
ymax = up),
position = position_jitterdodge(jitter.width = 0.005, jitter.height = 0, seed = jitter_seed)) +
geom_line(position = position_jitterdodge(jitter.width = 0.005, jitter.height = 0, seed = jitter_seed)) +
geom_point(size = 3, shape = 21, fill = "white",
position = position_jitterdodge(jitter.width = 0.005, jitter.height = 0, seed = jitter_seed)) +
stat_pvalue_manual(val, step.increase = 0.075,
label = "lab", size = 3.5,
y.position = 27) +
theme_bw(base_size = 16)
Created on 2023-04-28 with reprex v2.0.2
Would this approach work for your use-case?
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