I want to merge two legends in ggplot2. I use the following code:
ggplot(dat_ribbon, aes(x = x)) +
geom_ribbon(aes(ymin = ymin, ymax = ymax,
group = group, fill = "test4 test5"), alpha = 0.2) +
geom_line(aes(y = y, color = "Test2"), data = dat_m) +
scale_colour_manual(values=c("Test2" = "white", "test"="black", "Test3"="red")) +
scale_fill_manual(values = c("test4 test5"= "dodgerblue4")) +
theme(legend.title=element_blank(),
legend.position = c(0.8, 0.85),
legend.background = element_rect(fill="transparent"),
legend.key = element_rect(colour = 'purple', size = 0.5))
The output is shown below. There are two problems:
When I use two or more words in the fill legend, the alignment becomes wrong
I want to merge the two legends into one, such that the fill legend is just part of a block of 4.
Does anyone know how I can achieve this?
Edit: reproducible data:
dat_m <- read.table(text="x quantile y group
1 1 50 0.4967335 0
2 2 50 0.4978249 0
3 3 50 0.5113562 0
4 4 50 0.4977866 0
5 5 50 0.5013287 0
6 6 50 0.4997994 0
7 7 50 0.4961121 0
8 8 50 0.4991302 0
9 9 50 0.4976087 0
10 10 50 0.5011666 0")
dat_ribbon <- read.table(text="
x ymin group ymax
1 1 0.09779713 40 0.8992385
2 2 0.09979283 40 0.8996875
3 3 0.10309222 40 0.9004759
4 4 0.10058433 40 0.8985366
5 5 0.10259125 40 0.9043807
6 6 0.09643109 40 0.9031940
7 7 0.10199870 40 0.9022920
8 8 0.10018253 40 0.8965690
9 9 0.10292754 40 0.9010934
10 10 0.09399359 40 0.9053067
11 1 0.20164694 30 0.7974174
12 2 0.20082056 30 0.7980642
13 3 0.20837821 30 0.8056074
14 4 0.19903399 30 0.7973723
15 5 0.19903322 30 0.8050146
16 6 0.19965049 30 0.8051922
17 7 0.20592719 30 0.8042850
18 8 0.19810139 30 0.7956606
19 9 0.20537392 30 0.8007527
20 10 0.19325158 30 0.8023044
21 1 0.30016463 20 0.6953927
22 2 0.29803646 20 0.6976961
23 3 0.30803808 20 0.7048137
24 4 0.30045448 20 0.6991248
25 5 0.29562249 20 0.7031225
26 6 0.29647060 20 0.7043499
27 7 0.30159103 20 0.6991356
28 8 0.30369025 20 0.6949053
29 9 0.30196483 20 0.6998127
30 10 0.29578036 20 0.7015861
31 1 0.40045725 10 0.5981147
32 2 0.39796299 10 0.5974115
33 3 0.41056038 10 0.6057062
34 4 0.40046287 10 0.5943157
35 5 0.39708008 10 0.6014512
36 6 0.39594129 10 0.6011162
37 7 0.40052411 10 0.5996186
38 8 0.40128517 10 0.5959748
39 9 0.39917658 10 0.6004600
40 10 0.39791453 10 0.5999168")
You are not using ggplot2 according to its philosophy. That makes things difficult.
ggplot(dat_ribbon, aes(x = x)) +
geom_ribbon(aes(ymin = ymin, ymax = ymax, group = group, fill = "test4 test5"),
alpha = 0.2) +
geom_line(aes(y = y, color = "Test2"), data = dat_m) +
geom_blank(data = data.frame(x = rep(5, 4), y = 0.5,
group = c("test4 test5", "Test2", "test", "Test3")),
aes(y = y, color = group, fill = group)) +
scale_color_manual(name = "combined legend",
values=c("test4 test5"= NA, "Test2" = "white",
"test"="black", "Test3"="red")) +
scale_fill_manual(name = "combined legend",
values = c("test4 test5"= "dodgerblue4",
"Test2" = NA, "test"=NA, "Test3"=NA))
Related
This question already has an answer here:
Annotation on only the first facet of ggplot in R?
(1 answer)
Closed last month.
I want to add a few texts in one facet out of four facets in my ggplot.
I am using annotate function to add a text but it generates the text at a given location (x,y) in every facet. Because the data variables have different ranges of y in each facet, the texts are not coming at a desired location (x,y).
Please let me know what should be done. Thanks.
library(dplyr)
library(tidyr)
library(ggplot2)
df%>%
select(Date, Ca, Na, K, Mg)%>%
gather(var,value,-Date)%>%
ggplot(aes(as.Date(Date), value))+
geom_point()+
theme_bw()+
facet_wrap(~var,scales = 'free_y',ncol = 1)+
ylab(" (ppm) (ppm)
(ppm) (ppm)")+
facet_wrap(~var,scales = 'free_y',ncol = 1, strip.position = "right")+
geom_vline(aes(xintercept = as.Date("2021-04-28")), col = "red")+
geom_vline(aes(xintercept = as.Date("2021-04-28")), col = "red")+
geom_vline(aes(xintercept = as.Date("2021-04-29")), col = "red")+
theme(axis.title = element_text(face="bold"))+
theme(axis.text = element_text(face="bold"))+
xlab('Date')+
theme(axis.title.x = element_text(margin = margin(t = 10)))+
theme(axis.title.y = element_text(margin = margin(r = 10)))+
annotate("text", label = "E1", x = as.Date("2021-04-28"), y = 2.8)
This is the code I am using for the desired output. I want to name all the xintercept lines which is E1, E2, E3 (from left to right) on the top of xaxis i.e. above the first facet of variable Ca in the data. Any suggestions?
Here is a part of my data:
df <- read.table(text = "
Date Ca K Mg Na
2/18/2021 1 25 21 19
2/22/2021 2 26 22 20
2/26/2021 3 27 23 21
3/4/2021 4 28 5 22
3/6/2021 5 29 6 8
3/10/2021 6 30 7 9
3/13/2021 7 31 8 10
3/17/2021 8 32 9 11
3/20/2021 9 33 10 12
3/23/2021 10 34 11 13
3/27/2021 11 35 12 14
3/31/2021 12 36 13 15
4/3/2021 13 37 14 16
4/7/2021 14 38 15 17
4/10/2021 15 39 16 18
4/13/2021 16 40 17 19
4/16/2021 17 41 18 20
4/19/2021 8 42 19 21
4/22/2021 9 43 20 22
4/26/2021 0 44 21 23
4/28/2021 1 45 22 24
4/28/2021 2 46 23 25
4/28/2021 3 47 24 26
4/28/2021 5 48 25 27
4/29/2021 6 49 26 28
5/4/2021 7 50 27 29
5/7/2021 8 51 28 30
5/8/2021 9 1 29 31
5/10/2021 1 2 30 32
5/29/2021 3 17 43 45
5/31/2021 6 18 44 46
6/1/2021 4 19 45 47
6/2/2021 8 20 46 48
6/3/2021 2 21 47 49
6/7/2021 3 22 48 50
6/10/2021 5 23 49 51
6/14/2021 3 5 50 1
6/18/2021 1 6 51 2
", header = TRUE)
Prepare the data before plotting, make a separate data for text annotation:
dfplot <- df %>%
select(Date, Ca, Na, K, Mg) %>%
#convert to date class before plotting
mutate(Date = as.Date(Date, "%m/%d/%Y")) %>%
#using pivot instead of gather. gather is superseded.
#gather(var, value, -Date)
pivot_longer(cols = 2:5, names_to = "grp", values_to = "ppm")
dftext <- data.frame(grp = "Ca", # we want text to show up only on "Ca" facet.
ppm = max(dfplot[ dfplot$grp == "Ca", "ppm" ]),
Date = as.Date(c("2021-04-27", "2021-04-28", "2021-04-29")),
label = c("E1", "E2", "E3"))
After cleaning up your code, we can use geom_text with dftext:
ggplot(dfplot, aes(Date, ppm)) +
geom_point() +
facet_wrap(~grp, scales = 'free_y',ncol = 1, strip.position = "right") +
geom_vline(xintercept = dftext$Date, col = "red") +
geom_text(aes(x = Date, y = ppm, label = label), data = dftext, nudge_y = -2)
Try using ggrepel library to avoid label overlap, replace geom_text with one of these:
#geom_text_repel(aes(x = Date, y = ppm, label = label), data = dftext)
#geom_label_repel(aes(x = Date, y = ppm, label = label), data = dftext)
After cleaning up the code and seeing the plot, I think this post is a duplicate of Annotation on only the first facet of ggplot in R? .
I was trying to plot a time series composed of weekly averanges. Here is the plot that I have obtained:
[weekly averages A]
[1]: https://i.stack.imgur.com/XMGMs.png
As you can see the time serie do not cover all the years completely, so, when I have got no data ggplot links two subsequent years. I think I have to group the data in some ways, but I do not understand how. Here is the code:
df4 <- data.frame(df$Date, df$A)
colnames(df4)<- c("date","A")
df4$date <- as.Date(df4$date,"%Y/%m/%d")
df4$week_day <- as.numeric(format(df4$date, format='%w'))
df4$endofweek <- df4$date + (6 - df4$week_day)
week_aveA <- df4 %>%
group_by(endofweek) %>%
summarise_all(list(mean=mean), na.rm=TRUE) %>%
na.omit()
g1 = ggplot() +
geom_step(data=week_aveA, aes(group = 1, x = (endofweek), y = (A_mean)), colour="gray25") +
scale_y_continuous(expand = c(0, 0), limits = c(0, 2500)) +
scale_x_date(breaks="year", labels=date_format("%Y")) +
labs(y = expression(A~ ~index),
x = NULL) +
theme(axis.text.x = element_text(size=10),
axis.title = element_text(size=10))
Here an extraction (the former three years) of the dataset:
endofweek date_mean A_mean week_day_mean
1 20/03/2010 17/03/2010 939,2533437 3
2 27/03/2010 24/03/2010 867,3620121 3
3 03/04/2010 31/03/2010 1426,791222 3
4 10/04/2010 07/04/2010 358,5698314 3
5 17/04/2010 13/04/2010 301,1815352 2
6 24/04/2010 21/04/2010 273,4922895 3,333333333
7 01/05/2010 28/04/2010 128,5989633 3
8 08/05/2010 05/05/2010 447,8858881 3
9 15/05/2010 12/05/2010 387,9828891 3
10 22/05/2010 19/05/2010 138,0770986 3
11 29/05/2010 26/05/2010 370,2147933 3
12 05/06/2010 02/06/2010 139,0451791 3
13 12/06/2010 09/06/2010 217,1286356 3
14 19/06/2010 16/06/2010 72,36972411 3
15 26/06/2010 23/06/2010 282,2911902 3
16 03/07/2010 30/06/2010 324,3215936 3
17 10/07/2010 07/07/2010 210,568691 3
18 17/07/2010 14/07/2010 91,76930829 3
19 24/07/2010 21/07/2010 36,4211218 3,666666667
20 31/07/2010 28/07/2010 37,53981103 3
21 07/08/2010 04/08/2010 91,33282642 3
22 14/08/2010 11/08/2010 28,38587352 3
23 21/08/2010 18/08/2010 58,72836406 3
24 28/08/2010 24/08/2010 102,1050612 2,5
25 04/09/2010 02/09/2010 13,45357513 4,5
26 11/09/2010 08/09/2010 51,24017212 3
27 18/09/2010 15/09/2010 159,7395663 3
28 25/09/2010 21/09/2010 62,71136678 2
29 02/04/2011 31/03/2011 1484,661164 4
30 09/04/2011 06/04/2011 656,1827964 3
31 16/04/2011 13/04/2011 315,3097313 3
32 23/04/2011 20/04/2011 293,2904042 3
33 30/04/2011 26/04/2011 255,7517519 2,4
34 07/05/2011 04/05/2011 360,7035289 3
35 14/05/2011 11/05/2011 342,0902797 3
36 21/05/2011 18/05/2011 386,1380421 3
37 28/05/2011 24/05/2011 418,9624807 2,833333333
38 04/06/2011 01/06/2011 112,7568 3
39 11/06/2011 08/06/2011 85,17855619 3,2
40 18/06/2011 15/06/2011 351,8714638 3
41 25/06/2011 22/06/2011 139,7936898 3
42 02/07/2011 29/06/2011 68,57716191 3,6
43 09/07/2011 06/07/2011 62,31823822 3
44 16/07/2011 13/07/2011 80,7328917 3
45 23/07/2011 20/07/2011 114,9475331 3
46 30/07/2011 27/07/2011 90,13118758 3
47 06/08/2011 03/08/2011 43,29372258 3
48 13/08/2011 10/08/2011 49,39935204 3
49 20/08/2011 16/08/2011 133,746822 2
50 03/09/2011 31/08/2011 76,03928942 3
51 10/09/2011 05/09/2011 27,99834637 1
52 24/03/2012 23/03/2012 366,2625797 5,5
53 31/03/2012 28/03/2012 878,8535513 3
54 07/04/2012 04/04/2012 1029,909052 3
55 14/04/2012 11/04/2012 892,9163416 3
56 21/04/2012 18/04/2012 534,8278693 3
57 28/04/2012 25/04/2012 255,1177585 3
58 05/05/2012 02/05/2012 564,5280546 3
59 12/05/2012 09/05/2012 767,5018168 3
60 19/05/2012 16/05/2012 516,2680148 3
61 26/05/2012 23/05/2012 241,2113073 3
62 02/06/2012 30/05/2012 863,6123397 3
63 09/06/2012 06/06/2012 201,2019288 3
64 16/06/2012 13/06/2012 222,9955486 3
65 23/06/2012 20/06/2012 91,14166632 3
66 30/06/2012 27/06/2012 26,93145693 3
67 07/07/2012 04/07/2012 67,32183278 3
68 14/07/2012 11/07/2012 46,25297513 3
69 21/07/2012 18/07/2012 81,34359825 3,666666667
70 28/07/2012 25/07/2012 49,59130851 3
71 04/08/2012 01/08/2012 44,13438077 3
72 11/08/2012 08/08/2012 30,15773151 3
73 18/08/2012 15/08/2012 57,47256772 3
74 25/08/2012 22/08/2012 31,9109555 3
75 01/09/2012 29/08/2012 52,71058484 3
76 08/09/2012 04/09/2012 24,52495229 2
77 06/04/2013 01/04/2013 1344,388042 1,5
78 13/04/2013 10/04/2013 1304,838687 3
79 20/04/2013 17/04/2013 892,620141 3
80 27/04/2013 24/04/2013 400,1720434 3
81 04/05/2013 01/05/2013 424,8473083 3
82 11/05/2013 08/05/2013 269,2380208 3
83 18/05/2013 15/05/2013 238,9993749 3
84 25/05/2013 22/05/2013 128,4096151 3
85 01/06/2013 29/05/2013 158,5576121 3
86 08/06/2013 05/06/2013 175,2036942 3
87 15/06/2013 12/06/2013 79,20250839 3
88 22/06/2013 19/06/2013 126,9065428 3
89 29/06/2013 26/06/2013 133,7480108 3
90 06/07/2013 03/07/2013 218,0092943 3
91 13/07/2013 10/07/2013 54,08460936 3
92 20/07/2013 17/07/2013 91,54285041 3
93 27/07/2013 24/07/2013 44,64567928 3
94 03/08/2013 31/07/2013 229,5067999 3
95 10/08/2013 07/08/2013 49,70729373 3
96 17/08/2013 14/08/2013 53,38618335 3
97 24/08/2013 21/08/2013 217,2800997 3
98 31/08/2013 28/08/2013 49,43590136 3
99 07/09/2013 04/09/2013 64,88783029 3
100 14/09/2013 11/09/2013 11,04300773 3
So at the end I have one mainly question: how can I eliminated the connection between the years? ... and an aesthetic question: how can I add minor ticks on the x_axis? At least one every 6 months, just to make the plot easy to read.
Thanks in advance for any suggestion!
Edit
This is the code I tried with the suggestion, maybe I mistype some part of it.
library(tidyverse)
library(dplyr)
library(lubridate)
df4 <- data.frame(df$Date, df$A)
colnames(df4)<- c("date","A")
df4$date <- as.Date(df4$date,"%Y/%m/%d")
df4$week_day <- as.numeric(format(df4$date, format='%w'))
df4$endofweek <- df4$date + (6 - df4$week_day)
week_aveA <- df4 %>%
group_by(endofweek) %>%
summarise_all(list(mean=mean), na.rm=TRUE) %>%
na.omit()
week_aveA$endofweek <- as.Date(week_aveA$endofweek,"%d/%m/%Y")
week_aveA$A_mean <- as.numeric(gsub(",", ".", week_aveA$A_mean))
week_aveA$week_day_mean <- as.numeric(gsub(",", ".", week_aveA$week_day_mean))
week_aveA$year <- format(week_aveA$endofweek, "%Y")
library(ggplot2)
library(methods)
library(scales)
mylabel <- function(x) {
ifelse(grepl("-07-01$", x), "", format(x, "%Y"))
}
ggplot() +
geom_step(data=week_aveA, aes(x = endofweek, y = A_mean, group = year), colour="gray25") +
scale_y_continuous(expand = c(0, 0), limits = c(0, 2500)) +
scale_x_date(breaks="6 month", labels = mylabel) +
labs(y = expression(A~ ~index),
x = NULL) +
theme(axis.text.x = element_text(size=10),
axis.title = element_text(size=10))
You have to group by year:
Add a variable with the year to your dataset
Map the year variable on the group aesthetic
For the ticks. Increase the number of the breaks. If you want only ticks but not labels you can use a custom function to get rid of unwanted labels, e.g. my approach below set the breaks to "6 month" but replaces the mid-year labels with an empty string:
week_aveA$endofweek <- as.Date(week_aveA$endofweek,"%d/%m/%Y")
week_aveA$A_mean <- as.numeric(gsub(",", ".", week_aveA$A_mean))
week_aveA$week_day_mean <- as.numeric(gsub(",", ".", week_aveA$week_day_mean))
week_aveA$year <- format(week_aveA$endofweek, "%Y")
library(ggplot2)
mylabel <- function(x) {
ifelse(grepl("-07-01$", x), "", format(x, "%Y"))
}
ggplot() +
geom_step(data=week_aveA, aes(x = endofweek, y = A_mean, group = year), colour="gray25") +
scale_y_continuous(expand = c(0, 0), limits = c(0, 2500)) +
scale_x_date(breaks="6 month", labels = mylabel) +
labs(y = expression(A~ ~index),
x = NULL) +
theme(axis.text.x = element_text(size=10),
axis.title = element_text(size=10))
I have been trying to plot some data on the map.
With the plot circle of the observed data changing according to a scale.
But the plot produced doesn't reflect the scale.
See the following.
This is the code which I have tried.
newmap <- get_map(location = c(lon = 82.5,lat = 24),zoom=4, color="bw")
ggmap(newmap, extent = "normal") +
geom_point(aes(x = lon, y = lat, colour = scale , size = scale), data = final_data)
I got the code from the following post.
My data looks like this.
> final_data
lon lat disab scale
1 74.79728 34.083671 27832 1
2 74.87226 31.633979 28119 1
3 75.85728 30.900965 34830 1
4 77.31779 28.408912 33579 1
5 77.10249 28.704059 228427 6
6 75.78727 26.912434 74541 2
7 73.02431 26.238947 24898 1
8 75.86475 25.213816 20843 1
9 77.70641 28.984462 27864 1
10 77.45376 28.669156 84458 2
11 78.00807 27.176670 54382 2
12 80.94617 26.846694 77684 2
13 80.33187 26.449923 81988 2
14 81.84631 25.435801 37750 1
15 82.97391 25.317645 39408 2
16 85.13756 25.594095 68869 2
17 86.95240 23.673945 24627 1
18 88.36390 22.572646 342319 8
19 86.43039 23.795653 28865 1
20 86.20288 22.804566 20766 1
21 85.30956 23.344100 22957 1
22 81.28492 21.190449 22061 1
23 81.62964 21.251384 25868 1
24 78.18283 26.218287 18434 1
25 75.85773 22.719569 56279 2
26 77.41262 23.259933 73219 2
27 79.98641 23.181467 32597 1
28 72.57136 23.022505 188917 5
29 70.80216 22.303894 20219 1
30 73.18122 22.307159 47587 2
31 72.83106 21.170240 55055 2
32 75.34331 19.876165 36205 1
33 79.08815 21.145800 63969 2
34 73.78980 19.997453 26572 1
35 72.83973 19.391928 37382 1
36 72.81771 19.003050 484688 11
37 73.85674 18.520430 127858 3
38 78.48667 17.385044 294072 7
39 80.64802 16.506174 40592 2
40 NA NA 53865 2
41 77.61586 12.941483 251561 6
42 75.37037 11.874477 33907 1
43 75.78041 11.258753 51981 2
44 76.07400 11.073182 31863 1
45 76.21443 10.527642 38573 2
46 76.26730 9.931233 41432 2
47 76.61414 8.893212 23403 1
48 76.93664 8.524139 39024 2
49 80.27072 13.082680 163428 4
50 78.70467 10.790483 14489 1
51 78.11978 9.925201 19890 1
52 76.95583 11.016844 32794 1
It will be ton of help, if someone can help me figure out the problem..:)
Thanks in advance.
It does not work because there is no myscale column in your data:final_data.
Change myscale to scale:
newmap <- get_map(location = c(lon = 82.5,lat = 24),zoom=4, color="bw")
ggmap(newmap, extent = "normal") +
geom_point(aes(x = lon, y = lat, colour = scale , size = scale), data = final_data)
Plotting my data in R with ggplot, the error bar whiskers are not displayed. Why are the whiskers not displayed and what is the fix so they will be displayed?
(Though it is not necessary to specify "data=..." in geom_errorbar, I am using a smaller set of data to plot a few points and their error bars on top of a larger set of data. I simplified here to just use the smaller data frame for everything but want to keep this example close to the code I intend to use.)
Thanks!
Shawna
shapes <- c(1, 19, 15, 1, 0)
names(shapes) <- levels(smallDF$Treatment)
p <- ggplot(data=smallDF, aes(x=pNew, y=diff, group=Treatment))
p <- p + geom_errorbar(data=smallDF, aes(ymin=diff-se,ymax=diff+se),
color="black", width=.3, position=position_dodge(.5))
p <- p + geom_line(size=.3)
p <- p + geom_point(data=smallDF, aes(shape=Treatment),fill="white",
size=2.5)
#p <- p + scale_shape_manual(values=c(1, 19, 15, 1, 0))
p <- p + scale_shape_manual(values=shapes)
p <- p + xlab("Pressure (mmHg)") + ylab("delD (mm)")
p <- p + theme_bw()
p <- p + theme(
legend.position="none"
# , axis.text.y=element_blank()
# , axis.title.y=element_blank()
, panel.border=element_blank()
, axis.line = element_line(colour = "black")
, axis.text.x = element_text(size=10)
, axis.text.y = element_text(size=10)
, axis.title.x= element_text(size=10)
, axis.title.y= element_text(size=10)
, strip.text.x = element_text(size = 10)
)
p
Treatment step N diff sd se ci predictD pNew
cntl 2 7 0.256537749 0.130605763 0.049364339 0.120790185 1.483185156 10
cntl 3 7 0.317586245 0.151444256 0.057240549 0.140062577 1.626590815 15
cntl 4 7 0.377309785 0.165262839 0.062463482 0.152842634 1.788401781 20
cntl 5 7 0.433531627 0.173735352 0.065665791 0.160678402 1.964393744 25
cntl 6 7 0.467529177 0.171603123 0.064859884 0.158706419 2.142879696 30
cntl 7 7 0.441401156 0.163740786 0.0618882 0.15143497 2.291729181 35
cntl 8 7 0.360578168 0.143967074 0.054414439 0.133147337 2.402152991 40
cntl 9 7 0.263484929 0.117425017 0.044382485 0.108600028 2.481824239 45
cntl 10 7 0.172079736 0.094209661 0.035607905 0.087129405 2.53504158 50
cntl 11 7 0.081780331 0.070316765 0.026577239 0.065032161 2.561500546 55
cntl 12 7 0.172079736 0.094209661 0.035607905 0.087129405 2.53504158 50
cntl 13 7 0.263484929 0.117425017 0.044382485 0.108600028 2.481824239 45
cntl 14 7 0.360578168 0.143967074 0.054414439 0.133147337 2.402152991 40
cntl 15 7 0.441401156 0.163740786 0.0618882 0.15143497 2.291729181 35
cntl 16 7 0.467529177 0.171603123 0.064859884 0.158706419 2.142879696 30
cntl 17 7 0.433531627 0.173735352 0.065665791 0.160678402 1.964393744 25
cntl 18 7 0.377309785 0.165262839 0.062463482 0.152842634 1.788401781 20
cntl 19 7 0.317586245 0.151444256 0.057240549 0.140062577 1.626590815 15
cntl 20 7 0.256537749 0.130605763 0.049364339 0.120790185 1.483185156 10
3hpx 2 6 0.124643574 0.068765439 0.028073373 0.072164903 1.511618688 10
3hpx 3 8 0.121806932 0.088542241 0.03130441 0.074023166 1.537544183 15
3hpx 4 8 0.138107729 0.097228081 0.034375318 0.08128471 1.602344034 20
3hpx 5 8 0.149529 0.10158369 0.035915258 0.08492609 1.665227481 25
3hpx 6 8 0.157687817 0.101898303 0.036026491 0.085189113 1.724788023 30
3hpx 7 8 0.154261671 0.099724849 0.035258058 0.08337206 1.776475381 35
3hpx 8 8 0.140631071 0.091483297 0.03234423 0.07648195 1.819131367 40
3hpx 9 8 0.123241311 0.083112381 0.029384664 0.069483689 1.854326249 45
3hpx 10 8 0.103092334 0.075467614 0.026681831 0.063092504 1.882440312 50
3hpx 11 8 0.080332775 0.070303352 0.024855989 0.058775073 1.903587298 55
3hpx 12 8 0.103092334 0.075467614 0.026681831 0.063092504 1.882440312 50
3hpx 13 8 0.123241311 0.083112381 0.029384664 0.069483689 1.854326249 45
3hpx 14 8 0.140631071 0.091483297 0.03234423 0.07648195 1.819131367 40
3hpx 15 8 0.154261671 0.099724849 0.035258058 0.08337206 1.776475381 35
3hpx 16 8 0.157687817 0.101898303 0.036026491 0.085189113 1.724788023 30
3hpx 17 8 0.149529 0.10158369 0.035915258 0.08492609 1.665227481 25
3hpx 18 8 0.138107729 0.097228081 0.034375318 0.08128471 1.602344034 20
3hpx 19 8 0.121806932 0.088542241 0.03130441 0.074023166 1.537544183 15
3hpx 20 6 0.124643574 0.068765439 0.028073373 0.072164903 1.511618688 10
I changed your width = 0.3 to width = 5. I also deleted all the redundant data = smallDF that you had and replaced your individually-set font sizes with the base_size argument of theme_bw().
p <- ggplot(data = smallDF, aes(x = pNew, y = diff, group = Treatment)) +
geom_errorbar(aes(ymin = diff - se, ymax = diff + se),
color = "black",
width = 5, ## This is the width of the crossbars!
position = position_dodge(.5))
geom_line(size = .3)
geom_point(aes(shape = Treatment),
fill = "white", size = 2.5) +
scale_shape_manual(values = shapes) +
xlab("Pressure (mmHg)") +
ylab("delD (mm)") +
theme_bw(base_size = 10) +
theme(
legend.position="none"
, panel.border=element_blank()
, axis.line = element_line(colour = "black")
)
p
I am using both geom_hist and histogram in R with the same breakpoints but I get different graphs. I did a quick search, does anyone know what the definition breaks are and why they would be a difference
These produce two different plots.
set.seed(25)
data <- data.frame(Mos=rnorm(500, mean = 25, sd = 8))
data$Mos<-round(data$Mos)
pAge <- ggplot(data, aes(x=Mos))
pAge + geom_histogram(breaks=seq(0, 50, by = 2))
hist(data$Mos,breaks=seq(0, 50, by = 2))
Thanks
To get the same histogram in ggplot2 you specify the breaks inside scale_x_continuous and binwidth inside geom_histogram.
Additionally, hist and histograms in ggplot2 use different defaults to create the intervals:
hist: right-closed (left open) intervals. Default: right = TRUE
stat_bin (ggplot2): left-closed (right open) intervals. Default: right = FALSE
**hist** **ggplot2**
freq1 Freq freq2 Freq
1 (0,2] 0 [0,2) 0
2 (2,4] 2 [2,4) 2
3 (4,6] 2 [4,6) 1
4 (6,8] 1 [6,8) 2
5 (8,10] 6 [8,10) 2
6 (10,12] 9 [10,12) 7
7 (12,14] 24 [12,14) 17
8 (14,16] 27 [14,16) 26
9 (16,18] 39 [16,18) 31
10 (18,20] 48 [18,20) 46
11 (20,22] 52 [20,22) 43
12 (22,24] 38 [22,24) 57
13 (24,26] 44 [24,26) 36
14 (26,28] 46 [26,28) 52
15 (28,30] 39 [28,30) 39
16 (30,32] 31 [30,32) 33
17 (32,34] 30 [32,34) 26
18 (34,36] 24 [34,36) 29
19 (36,38] 18 [36,38) 27
20 (38,40] 9 [38,40) 12
21 (40,42] 5 [40,42) 6
22 (42,44] 4 [42,44) 0
23 (44,46] 1 [44,46) 5
24 (46,48] 1 [46,48) 0
25 (48,50] 0 [48,50) 1
I included the argument right = FALSE so the histogram intervalss are left-closed (right open) as they are in ggplot2. I added the labels in both plots, so it is easier to check the intervals are the same.
ggplot(data, aes(x = Mos))+
geom_histogram(binwidth = 2, colour = "black", fill = "white")+
scale_x_continuous(breaks = seq(0, 50, by = 2))+
stat_bin(binwidth = 2, aes(label=..count..), vjust=-0.5, geom = "text")
hist(data$Mos,breaks=seq(0, 50, by = 2), labels =TRUE, right =FALSE)
To check the frequencies in each bin:
freq <- cut(data$Mos, breaks = seq(0, 50, by = 2), dig.lab = 4, right = FALSE)
as.data.frame(table(frecuencias))