passing multiple arguments to a function consisting of ggplot - r

Hi I have this piece of code that I use again and again
ggplot(foo1, aes(x=log(area), y=log(fd), colour = id)) +
geom_point()+
scale_color_manual(name = "Regions",values=cols)+
xlab('John')+
ylab('Peter')+
ggtitle("xyz")+
ggsave("x.png")
And I wrote this:
my.function<-function(arg1,arg2,arg3){
ggplot(arg1, aes_string(x=arg2, y=arg3, colour = id)) +
geom_point()+
scale_color_manual(name = "Regions",values=cols)+
xlab('John')+
ylab('Peter')+
ggtitle("xyz")+
ggsave("x.png")
}
I am calling this way
my.function(arg1='foo1',arg2='log(area)',arg3='log(fd)')
But it doesn't work. I have never written functions before. I want to save the figure in every function call. Could you please help?
dput(head(foo1,4))
structure(list(id = structure(c(1L, 1L, 1L, 1L), .Label = c("dfa",
"dfb", "cfa", "csb", "bsk"), class = "factor"), lon = c(-70.978611,
-70.978611, -70.945278, -70.945278), lat = c(42.220833, 42.220833,
42.190278, 42.190278), peakq = c(14.7531, 17.3865, 3.3414, 2.7751
), area = c(74.3327, 74.3327, 11.6549, 11.6549), fd = c(29, 54.75,
23, 1), tp = c(14.25, 19.75, 13.5, 0.5), rt = c(14.75, 35, 9.5,
0.5), bl = c(15485.3, 15485.3, 8242.64, 8242.64), el = c(0.643551,
0.643551, 0.474219, 0.474219), k = c(0.325279, 0.325279, 0.176624,
0.176624), r = c(81.947, 81.947, 38.7003, 38.7003), si = c(0.0037157,
0.0037157, -9999, -9999), rr = c(0.00529193, 0.00529193, 0.00469513,
0.00469513)), .Names = c("id", "lon", "lat", "peakq", "area",
"fd", "tp", "rt", "bl", "el", "k", "r", "si", "rr"), row.names = c(NA,
4L), class = "data.frame")

How about
my.function<-function(arg1,arg2,arg3){
ggplot(arg1, aes_string(x=arg2, y=arg3, colour ="id")) +
geom_point()+
scale_color_manual(name = "Regions",values=cols)+
xlab('John')+
ylab('Peter')+
ggtitle("xyz")+
ggsave("x.png")
}
and you call it with
my.function(arg1=foo1,arg2='log(area)',arg3='log(fd)')
Note that now you're passing the data.frame itself, not the name of the data.frame as a string. And since you're passing the column names as strings, you need to pass everything in aes_string as strings.
If you really want to pass the data.frame names as a string, you can change the first ggplot() call to
ggplot(get(arg1), aes_string(x=arg2, y=arg3, colour ="id")) +

Related

R: how to add significance differences between sub groups on a line plot

I have a line plot for 3 different groups and I would like to present on the chart, in addition to the significant differences, the significance of the differences between subgroups. For example, add the significance of the difference between each of the 3 populations' weights at age 1. I saw the stat_compare_means() function but failed to use it vertically between lines in my chart.
my current code:
library(tidyverse)
#pivot data into long format
df <- data.frame(
stringsAsFactors = FALSE,
ID = c(1L, 2L, 3L, 4L, 5L),
POPULATION = c("A", "A", "B", "B", "C"),
weight.at.age.1 = c(13.37, 5.19, 7.68, 6.96, 10.35),
weight.at.age.2 = c(14.15, 15.34, 6.92, 15.12, 8.86),
weight.at.age.3 = c(17.36, NA, 19.42, 36.39, 26.33)
) %>%
pivot_longer(cols = weight.at.age.1:weight.at.age.3,
names_to = 'age',
values_to = 'weight') %>%
mutate(age = str_remove(age, 'weight.at.age.'))
#plot data
ggline(data = df,
mapping = aes(x = age,
y = weight, add = "mean_se", color=POPULATION))+
stat_compare_means(aes(group = POPULATION), method = "anova", label = "p.signif",
label.y = c(56))
Tnx!

Using segment labels in ggplot with ggrepel with smooth segments

This is my dataframe:
df<-structure(list(year = c(1984, 1984), team = c("Australia", "Brazil"
), continent = c("Oceania", "Americas"), medal = structure(c(3L,
3L), .Label = c("Bronze", "Silver", "Gold"), class = "factor"),
n = c(84L, 12L)), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"))
And this is my ggplot (my question is related to the annotations regard Brazil label):
ggplot(data = df)+
geom_point(aes(x = year, y = n)) +
geom_text_repel(aes(x = year, y = n, label = team),
size = 3, color = 'black',
seed = 10,
nudge_x = -.029,
nudge_y = 35,
segment.size = .65,
segment.curvature = -1,
segment.angle = 178.975,
segment.ncp = 1)+
coord_flip()
So, I have a segment divided by two parts. On both parts I have 'small braks'. How can I avoid them?
I already tried to use segment.ncp, change nudge_xor nudge_ynut its not working.
Any help?
Not really sure what is going on here. This is the best I could generate by experimenting with variations to the input values for segment... arguments.
There is some guidance at: https://ggrepel.slowkow.com/articles/examples.html which has an example with shorter leader lines, maybe that's an approach you could use.
df<-structure(list(year = c(1984, 1984), team = c("Australia", "Brazil"
), continent = c("Oceania", "Americas"), medal = structure(c(3L,
3L), .Label = c("Bronze", "Silver", "Gold"), class = "factor"),
n = c(84L, 12L)), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"))
library(ggplot2)
library(ggrepel)
ggplot(data = df)+
geom_point(aes(x = year, y = n)) +
geom_text_repel(aes(x = year, y = n, label = team),
size = 3, color = 'black',
seed = 1,
nudge_x = -0.029,
nudge_y = 35,
segment.size = 0.5,
segment.curvature = -0.0000002,
segment.angle = 1,
segment.ncp = 1000)+
coord_flip()
Created on 2021-08-26 by the reprex package (v2.0.0)

How do I label the sum the total of y-axis column values from consecutive bar values like in the example “Confirmed” Cases per x-axis “Date”

I have been working on this for some time, and am re-posting this hoping to simplify the definition of the problem and to bring some clarity from feedback of my previous attempt. I am able to label each individual column value, but not able to put the code together necessary to sum the total. The examples I have looked at never work the way I try to put them together, for example with goup_by, or summarize etc.. I would like to only sum the values of "Confirmed Cases", and not show the other column values as with many c("x", "Y", ... "data"), it becomes impossible to read.
Here is the data frame:
dput(COVID1[1:12, ])
structure(list(COUNTY = c("Antrim", "Antrim", "Antrim", "Charlevoix",
"Charlevoix", "Grand Traverse", "Grand Traverse", "Grand Traverse",
"Antrim", "Grand Traverse", "Grand Traverse", "Grand Traverse"
), Date = structure(c(18453, 18456, 18457, 18453, 18455, 18453,
18456, 18457, 18455, 18453, 18456, 18457), class = "Date"), CASE_STATUS = c("Confirmed",
"Confirmed", "Confirmed", "Confirmed", "Confirmed", "Confirmed",
"Confirmed", "Confirmed", "Probable", "Probable", "Probable",
"Probable"), Cases = c(1L, 1L, 2L, 1L, 3L, 2L, 2L, 1L, 1L, 1L,
1L, 1L)), row.names = c(NA, 12L), class = "data.frame")
Code:
ggplot(filter(COVID1, COUNTY %in% c("Antrim", "Charlevoix", "Grand Traverse"), Cases > 0)) +
geom_col(aes(x = Date, y = Cases, fill = CASE_STATUS), position = position_stack(reverse = TRUE), width = .88)+
geom_text(aes(x = Date, y = Cases, label = (Cases)), position = position_stack(reverse = TRUE), vjust = 1.5, size = 3, color = "white") +
scale_fill_manual(values = c('blue',"tomato"))+
scale_x_date(labels = date_format("%m/%d"), limits = as.Date(c('2020-07-09','today()')), breaks = "1 week")+
theme(axis.text.x = element_text(angle=0))+
labs(title = "Antrim - Grand Traverse - Charlevoix")
I'm not sure if I understood the question but I think you want to add the sum of the confirmed cases as labels. There might be a ggplot way of doing it but I think the most straightforward way is to make another dataset with your labels and feed it in.
date_labels <- filter(COVID1, COUNTY %in% c("Antrim", "Charlevoix", "Grand Traverse"), Cases > 0) %>% group_by(Date) %>% summarise(confirmed_cases = sum(Cases[CASE_STATUS == "Confirmed"]))
ggplot(filter(COVID1, COUNTY %in% c("Antrim", "Charlevoix", "Grand Traverse"), Cases > 0)) +
geom_col(aes(x = Date, y = Cases, fill = CASE_STATUS), position = position_stack(reverse = TRUE), width = .88)+
geom_text(data = date_labels, aes(x = Date, y = 1, label = confirmed_cases), position = position_stack(reverse = TRUE), vjust = 1.5, size = 3, color = "white") +
scale_fill_manual(values = c('blue',"tomato"))+
scale_x_date(labels = label_date("%m/%d"), limits = as.Date(c('2020-07-09','today()')), breaks = "1 week")+
theme(axis.text.x = element_text(angle=0))+
labs(title = "Antrim - Grand Traverse - Charlevoix")
Gives me this result:

Error in ggtexttable (ggpubr)

I'm trying to create a publication-ready table using the ggtexttable function from ggpubr. I have a data frame:
dput(df)
structure(list(feature = list("start_codon", "stop_codon", "intergenic",
"3UTR", "5UTR", "exon", "intron", "ncRNA", "pseudogene"),
observed = list(structure(1L, .Names = "start_codon"), structure(1L, .Names = "stop_codon"),
structure(418L, .Names = "intergenic"), structure(48L, .Names = "3UTR"),
structure(28L, .Names = "5UTR"), structure(223L, .Names = "exon"),
structure(578L, .Names = "intron"), structure(20L, .Names = "ncRNA"),
structure(1L, .Names = "pseudogene")), expected = list(
0.286, 0.286, 369.02, 72.461, 33.165, 257.869, 631.189,
48.491, 3.172), fc = list(3.5, 3.5, 1.1, 0.7, 0.8, 0.9,
0.9, 0.4, 0.3), test = list("enrichment", "enrichment",
"enrichment", "depletion", "depletion", "depletion",
"depletion", "depletion", "depletion"), sig = list("F",
"F", "T", "T", "F", "T", "T", "T", "F"), p_val = list(
"0.249", "0.249", "0.00186", "0.00116", "0.209", "0.00814",
"0.00237", "<1e-04", "0.175")), class = "data.frame", row.names = c(NA,
-9L), .Names = c("feature", "observed", "expected", "fc", "test",
"sig", "p_val"))
And when I try to turn this into a table:
ggtexttable(df)
I get the error:
Error in (function (label, parse = FALSE, col = "black", fontsize =
12, : unused arguments (label.feature = dots[[5]][1],
label.observed = dots[[6]][1], label.expected = dots[[7]][1],
label.fc = dots[[8]][1], label.test = dots[[9]][1], label.sig_val
= dots[[10]][1], label.p_val = dots[[11]][1])
Does anyone know what might be causing this?
This works fine:
df <- head(iris)
ggtexttable(df)
I have found the problem and solution which is going to work for you. First of all your data is not in proper format (nested list) thats why you were getting this error trying to display it. You can check what is the format of the dataset easily by pasting in your console: str(data)
Here is the solution to convert your data to data.frame:
first.step <- lapply(data, unlist)
second.step <- as.data.frame(first.step, stringsAsFactors = F)
Then you can easily use the function ggtexttable(second.step) and it displays the table with your data.

error : ggplot2 doesn't know how to deal with data of class uneval

I have this code
ggplot() +
stat_density(kernel = "biweight",aes(x=fd, colour=id), data=foo1,position="identity",geom="line")+
coord_cartesian(xlim = c(0, 200))+
xlab("Flood Duration")+
ylab("Density")+
ggtitle("PDFs of Flood Duration")+
ggsave("pdf_fd_conus.png")
And I wrote this function
pdf.plot<-function(data,x,xl,yl,title,save){
ggplot() +
stat_density(data, kernel = "biweight",aes_string(x=x, colour='id'),
position="identity",geom="line")+
coord_cartesian(xlim = c(0, 200))+
xlab(xl)+
ylab(yl)+
ggtitle(title)+
ggsave(save)
}
Calling using this:
pdf.plot(data=foo1,x='fd',xl='b',
yl='a',title='a',save='y.png')
But I am getting this error:
Error: ggplot2 doesn't know how to deal with data of class uneval
Called from: eval(expr, envir, enclos)
This is dput(head(foo1,4))
structure(list(id = structure(c(1L, 1L, 1L, 1L), .Label = c("dfa",
"dfb", "cfa", "csb", "bsk"), class = "factor"), lon = c(-70.978611,
-70.978611, -70.945278, -70.945278), lat = c(42.220833, 42.220833,
42.190278, 42.190278), peakq = c(14.7531, 17.3865, 3.3414, 2.7751
), area = c(74.3327, 74.3327, 11.6549, 11.6549), fd = c(29, 54.75,
23, 1), tp = c(14.25, 19.75, 13.5, 0.5), rt = c(14.75, 35, 9.5,
0.5), bl = c(15485.3, 15485.3, 8242.64, 8242.64), el = c(0.643551,
0.643551, 0.474219, 0.474219), k = c(0.325279, 0.325279, 0.176624,
0.176624), r = c(81.947, 81.947, 38.7003, 38.7003), si = c(0.0037157,
0.0037157, -9999, -9999), rr = c(0.00529193, 0.00529193, 0.00469513,
0.00469513)), .Names = c("id", "lon", "lat", "peakq", "area",
"fd", "tp", "rt", "bl", "el", "k", "r", "si", "rr"), row.names = c(NA,
4L), class = "data.frame")
Could you please help?
Your problem is that you didn't specify what argument data is in stat_density. If you look at ?stat_density you'll see the first implied argument is actually mapping=. You need to change pdf.plot to:
pdf.plot<-function(data,x,xl,yl,title,save){
ggplot() +
stat_density(data = data, kernel = "biweight",aes_string(x=x, colour='id'),
position="identity",geom="line")+
coord_cartesian(xlim = c(0, 200))+
xlab(xl)+
ylab(yl)+
ggtitle(title)+
ggsave(save)
}

Resources