Related
I'm struggling to get polar_coords to work as I had hoped. I want each item to be represented by a coloured track, with a range of 1:50000. I then wanted to plot points over these tracks at the corresponding locations, with symbols representing the different categories. The points would then be annotated with the id.
Dataframe:
structure(list(item = structure(c(1L, 2L, 2L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 10L), .Label = c("AA", "AB", "AC", "AD", "AE",
"BA", "BB", "BC", "BD", "BE"), class = "factor"), location = c(10045L,
12041L, 15035L, 22054L, 19023L, 49411L, 39012L, 3041L, 23065L,
33015L, 42069L, 26859L), category = structure(c(1L, 1L, 2L, 3L,
1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L), .Label = c("X", "Y", "Z"), class = "factor"),
id = structure(c(1L, 8L, 2L, 7L, 6L, 10L, 5L, 1L, 1L, 3L,
4L, 9L), .Label = c("Apple", "Banana", "Cherry", "Grape",
"Mango", "Melon", "Orange", "Pear", "Raspberry", "Strawberry"
), class = "factor")), .Names = c("item", "location", "category",
"id"), class = "data.frame", row.names = c(NA, -12L))
my_data %>%
ggplot(aes(item, location, shape = category, label = id)) +
geom_col(aes(y = Inf), fill = "gray80") +
geom_point(size = 3) +
geom_text(vjust = -1) +
scale_x_discrete(expand = expand_scale(add = c(5,0))) +
coord_polar(theta = "y") +
theme_void()
If you want a break in the middle, you could change the item to a numeric value relating to it's desired position:
my_data %>%
mutate(item_pos = as.numeric(item),
item_pos = item_pos + if_else(item_pos > 5, 1, 0)) %>%
ggplot(aes(item_pos, location, shape = category, label = id)) +
...
Maybe you can work from this:
ggplot(data,aes(x=location, color=id, y=id)) +
geom_linerange(aes(y=id, xmin=0, xmax=50000, color=category), size=2, alpha=0.5) +
geom_point(size=3) +
coord_polar()
Given a dataframe as follows:
structure(list(city = structure(c(1L, 3L, 4L, 2L), .Label = c("bj",
"cq", "sh", "tj"), class = "factor"), area = c(1580.86, 1927.95,
532.24, 613.09), price = c(9.51, 94.42, 10.77, 8.58), level = structure(c(1L,
1L, 2L, 2L), .Label = c("a", "b"), class = "factor")), class = "data.frame", row.names = c(NA,
-4L))
I want to draw a scatter plot which x for area and y for price, at same time, the color of points only based on level, which means only two colors to distinguish a and b.
How could I draw this with ggplot2? Thanks.
You can use the following code for that
library(ggplot2)
ggplot(df, aes(x = area, y = price, col=level)) + geom_point()
ggplot(df, aes(x = area, y = price, col=level)) +
geom_point() +
ggrepel::geom_text_repel(aes(label = city))
Data
df=structure(list(city = structure(c(1L, 3L, 4L, 2L), .Label = c("bj",
"cq", "sh", "tj"), class = "factor"), area = c(1580.86, 1927.95,
532.24, 613.09), price = c(9.51, 94.42, 10.77, 8.58), level = structure(c(1L,
1L, 2L, 2L), .Label = c("a", "b"), class = "factor")), class = "data.frame", row.names = c(NA,
-4L))
I have problem ploting credibility interval like this:
My data structure is following，L1,L2,M,U1,U2 stand for 0.025quant,0.25quant,0.5quant,0.75quant,0.975quant,respectively.
`
structure(list(approach = structure(c(1L, 2L, 1L, 2L, 1L, 2L), class = "factor", .Label = c("INLA",
"rjags")), param = structure(c(1L, 2L, 3L, 1L, 2L, 3L), class = "factor", .Label = c("alpha",
"beta", "sig2")), L1 = c(0.0844546867936143, 1.79242348175439,
0.163143886545317, 0.0754165380733685, 1.79067991488052, 3.66675821267498
), L2 = c(0.60090835904286, 1.95337968870806, 0.898159977552433,
0.606017177641373, 1.95260448314298, 4.07080184844179), M = c(0.870204161297956,
2.03768437879748, 2.20651061559405, 0.87408237273113, 2.03725552264872,
4.32531027636171), U2 = c(1.13905085248391, 2.12210930874551,
4.26836270504725, 1.66260576926063, 2.28900567640091, 5.10063756831338
), U1 = c(1.65214011950274, 2.28396345192398, 4.9109804477583,
1.1450384685802, 2.12117799328209, 4.55657971279654), AP = structure(c(1L,
4L, 5L, 2L, 3L, 6L), .Label = c("INLA.alpha", "rjags.alpha",
"INLA.beta", "rjags.beta", "INLA.sig2", "rjags.sig2"), class = "factor")), .Names = c("approach",
"param", "L1", "L2", "M", "U2", "U1", "AP"), row.names = c(NA,
-6L), class = "data.frame")`
I referenced this answerenter link description here,but 'fill' seems only work for boxplot case.the code I tried so far is:
CI$AP=interaction(CI$approach,CI$param)
p=ggplot(CI,aes(y=AP))+geom_point(aes(x=M))
p=p+geom_segment(aes(x=L1,xend=U1,y=AP,yend=AP))
p=p+geom_segment(aes(x=L2,xend=U2,y=AP,yend=AP),size=1.5)
It is far away from what I want.
Many thanks!
How about the following:
ggplot(df, aes(x = param, y = M, colour = approach)) +
geom_point(position = position_dodge2(width = 0.3), size = 3) +
geom_linerange(
aes(ymin = L2, ymax = U2, x = param),
position = position_dodge2(width = 0.3),
size = 2) +
geom_linerange(
aes(ymin = L1, ymax = U1, x = param),
position = position_dodge2(width = 0.3),
size = 1) +
coord_flip() +
labs(x = "Parameter", y = "Estimate")
Sample data
df <- structure(list(approach = structure(c(1L, 2L, 1L, 2L, 1L, 2L), class = "factor", .Label = c("INLA",
"rjags")), param = structure(c(1L, 2L, 3L, 1L, 2L, 3L), class = "factor", .Label = c("alpha",
"beta", "sig2")), L1 = c(0.0844546867936143, 1.79242348175439,
0.163143886545317, 0.0754165380733685, 1.79067991488052, 3.66675821267498
), L2 = c(0.60090835904286, 1.95337968870806, 0.898159977552433,
0.606017177641373, 1.95260448314298, 4.07080184844179), M = c(0.870204161297956,
2.03768437879748, 2.20651061559405, 0.87408237273113, 2.03725552264872,
4.32531027636171), U2 = c(1.13905085248391, 2.12210930874551,
4.26836270504725, 1.66260576926063, 2.28900567640091, 5.10063756831338
), U1 = c(1.65214011950274, 2.28396345192398, 4.9109804477583,
1.1450384685802, 2.12117799328209, 4.55657971279654), AP = structure(c(1L,
4L, 5L, 2L, 3L, 6L), .Label = c("INLA.alpha", "rjags.alpha",
"INLA.beta", "rjags.beta", "INLA.sig2", "rjags.sig2"), class = "factor")), .Names = c("approach",
"param", "L1", "L2", "M", "U2", "U1", "AP"), row.names = c(NA,
-6L), class = "data.frame")
Hi have an experiment which consists of three variables, and I would like to plot them all on a single plot.
This is my df:
AB <- data.frame(block=c("A", "A", "A", "A", "B", "B", "B", "B" ),
familiarity=c("fam", "fam", "unfam", "unfam" ),
prime=c("P", "UP" ),
RT=c("570.6929", "628.7446", "644.6268", "607.4312", "556.3581", "645.4821", "623.5624", "604.4113"))
Right now I can only break one of the variables into two separate plots, like this where A and B are the two levels of the third variable:
A <- AB[which(AB$block == "A"),]
B <- AB[which(AB$block == "B"),]
pa <- ggplot(data=A, aes(x=prime, y=RT, group=familiarity)) +
geom_line(aes(linetype=familiarity), size=1) +
expand_limits(y=c(500,650))
pb <- ggplot(data=B, aes(x=prime, y=RT, group=familiarity)) +
geom_line(aes(linetype=familiarity), size=1) +
expand_limits(y=c(500,650))
I would like to superimpose plot A over plot B, and have this third variables to be identified by color.
Any ideas?
Is this what you mean?
p_all <- ggplot(AB, aes(x=prime,y=RT,group=interaction(familiarity,block))) +
geom_line(aes(linetype=familiarity,color=block))
Data used:
AB <- structure(list(block = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L), .Label = c("A", "B"), class = "factor"), familiarity = structure(c(1L,
1L, 2L, 2L, 1L, 1L, 2L, 2L), class = "factor", .Label = c("fam",
"unfam")), prime = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L
), class = "factor", .Label = c("P", "UP")), RT = c(570.6929,
628.7446, 644.6268, 607.4312, 556.3581, 645.4821, 623.5624, 604.4113
)), .Names = c("block", "familiarity", "prime", "RT"), row.names = c(NA,
-8L), class = "data.frame")
IF you have different datasets for those variables, then you can specify the data
ggplot()+
geom_line(data=A, aes(x=prime, y=RT, group=familiarity,linetype=familiarity), size=1) +
geom_line(data=B, aes(x=prime, y=RT, group=familiarity,linetype=familiarity), size=1)+
expand_limits(y=c(500,650))
I have an R dataframe data (made with dplyr) that I'm trying to plot with ggplot():
require(dplyr)
data <- structure(list(gGroup = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L), .Label = c("MC", "R", "UC"), class = "factor"),
Episode = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L), .Label = c("Morning", "Day", "Night", "24 hour"
), class = "factor"), variable = c("HF", "HF", "LF", "LF",
"HF", "HF", "LF", "LF", "HF", "HF", "LF", "LF"), parameter = c("RR",
"RT", "RR", "RT", "RR", "RT", "RR", "RT", "RR", "RT", "RR",
"RT"), mean = c(3.90575222833804, 4.24572828952087, 5.14491629837998,
3.88189313775535, 4.02908403079823, 3.91129824615597, 4.73913642980089,
3.63973850905423, 4.66445796048274, 4.21723744674943, 5.57765585365275,
4.01444148455851), sd = c(1.09129154084895, 1.43102672123806,
1.17782114274004, 1.33381488706382, 1.33497319178289, 1.22259231099975,
1.33329948427898, 1.09625319168102, 1.19876558625356, 1.73746797295816,
1.05862249404741, 1.91144835753868), se = c(0.199241664579179,
0.261268538538247, 0.215039736195078, 0.243520167060353,
0.471984298305965, 0.432251656867227, 0.471392553343098,
0.387584032867524, 0.215304655178374, 0.312058460044998,
0.190134212775724, 0.343306259564318)), .Names = c("gGroup",
"Episode", "variable", "parameter", "mean", "sd", "se"), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -12L), drop = TRUE, indices = list(
0:1, 2:3, 4:5, 6:7, 8:9, 10:11), group_sizes = c(2L, 2L,
2L, 2L, 2L, 2L), biggest_group_size = 2L, labels = structure(list(
gGroup = structure(c(1L, 1L, 2L, 2L, 3L, 3L), .Label = c("MC",
"R", "UC"), class = "factor"), Episode = structure(c(2L,
2L, 2L, 2L, 2L, 2L), .Label = c("Morning", "Day", "Night",
"24 hour"), class = "factor"), variable = c("HF", "LF", "HF",
"LF", "HF", "LF")), .Names = c("gGroup", "Episode", "variable"
), class = "data.frame", row.names = c(NA, -6L)))
Currently I'm using the following code to plot:
require(ggplot2)
require(ggthemes)
pd <- position_dodge(width=0.9)
p <- ggplot(data, aes(x = gGroup, y = mean, fill = variable)) +
facet_grid(parameter~Episode) +
geom_bar(stat="identity", position=pd) +
geom_errorbar(aes(ymin = mean-se, ymax = mean+se), width = .3, position=pd) +
theme_hc() + scale_fill_hc() +
labs(y = "Logit transform of spectral power (m/s2), mean±SE", x= NULL)
ann_text <- data.frame(gGroup = "MC", mean = 6, variable = "LF", parameter = "RR", Episode = "Day")
p + geom_text(aes(ymax = 6.5, width = .2), data = ann_text, label="*", position=pd)
This gives me the following plot:
I'm quite satisfied with the result, but as you can see the asterisk isn't aligned correctly. I looked it up online, and I read this and this and the manual.
Everyone I see the suggestions to use position=position_dodge(width=0.9), but this doesn't help for me. I tried hjust to maybe move the asterisk to the right position, but that's of no use either. Funny thing is that my error bars are aligned correctly.
I feel like I'm overlooking something very simple, but I cannot figure out what it is.
I'm using R 3.1.3 on OSX 10.10.2, and loading the newest versions of ggplot2 and ggthemes.
In order for position_dodge to work, there needs to be a reason to dodge. That is you need to change the ann_text appropriately with variable = c("LF", "HF"), so that there is a reason to dodge. Then just define the label appropriately. Below I assume you just want the * over the LF bar.
ann_text <- data.frame(gGroup = rep("MC",2),
mean = 6,
variable = c("LF", 'HF'),
label = c("*", ""),
parameter = "RR",
Episode = "Day")
p + geom_text(aes(ymax = 6.5, width = .2, label = label), data = ann_text, position=pd)