So here I what I want, I want to plot 4 columns (Standing, Sitting, Stepping, Cycling) vs Time, and have 1 plot per date. I also want the Y scale to be scaled between 0.5 and 4.5, BUT the Y axis be invisible and a legend saying which color is which.
Here is a sample of my data:
> head(graph_pre,30)
Date Time Axis1 Axis2 Axis3 VM Standing Stepping Cycling New_Sitting Counter
1 2022-05-10 2022-05-10 09:01:00 21 40 2 45.22 0 0 2 0 0
2 2022-05-10 2022-05-10 09:01:01 0 36 1 36.01 0 0 0 1 1
3 2022-05-10 2022-05-10 09:01:02 24 1 0 24.02 0 0 0 1 0
4 2022-05-10 2022-05-10 09:01:03 48 31 4 57.28 0 0 2 0 1
5 2022-05-10 2022-05-10 09:01:04 0 6 0 6.00 0 0 0 1 1
6 2022-05-10 2022-05-10 09:01:05 0 0 0 0.00 0 0 0 1 0
7 2022-05-10 2022-05-10 09:01:06 0 0 0 0.00 0 0 0 1 0
8 2022-05-10 2022-05-10 09:01:07 0 0 0 0.00 0 0 0 1 0
9 2022-05-10 2022-05-10 09:01:08 0 5 2 5.39 0 0 0 1 0
10 2022-05-10 2022-05-10 09:01:09 20 33 3 38.70 0 0 0 1 0
11 2022-05-10 2022-05-10 09:01:10 14 26 29 41.39 0 0 2 0 1
12 2022-05-10 2022-05-10 09:01:11 11 0 4 11.70 0 0 0 1 1
13 2022-05-10 2022-05-10 09:01:12 0 0 0 0.00 0 0 0 1 0
14 2022-05-10 2022-05-10 09:01:13 0 0 0 0.00 0 0 0 1 0
15 2022-05-10 2022-05-10 09:01:14 82 126 113 188.07 0 3 0 0 1
16 2022-05-10 2022-05-10 09:01:15 60 64 47 99.52 0 0 2 0 1
17 2022-05-10 2022-05-10 09:01:16 98 140 236 291.38 0 0 2 0 0
18 2022-05-10 2022-05-10 09:01:17 151 118 221 292.52 0 0 2 0 0
19 2022-05-10 2022-05-10 09:01:18 44 13 99 109.11 0 0 2 0 0
20 2022-05-10 2022-05-10 09:01:19 6 6 53 53.67 0 0 2 0 0
21 2022-05-10 2022-05-10 09:01:20 39 8 65 76.22 0 0 2 0 0
22 2022-05-10 2022-05-10 09:01:21 17 20 57 62.75 0 0 2 0 0
23 2022-05-10 2022-05-10 09:01:22 51 46 269 277.63 0 0 2 0 0
24 2022-05-10 2022-05-10 09:01:23 15 45 82 94.73 0 3 0 0 1
25 2022-05-10 2022-05-10 09:01:24 22 34 4 40.69 0 0 2 0 1
26 2022-05-10 2022-05-10 09:01:25 114 93 41 152.73 0 0 2 0 0
27 2022-05-10 2022-05-10 09:01:26 74 67 92 135.75 0 0 2 0 0
28 2022-05-10 2022-05-10 09:01:27 117 9 40 123.98 0 0 2 0 0
29 2022-05-10 2022-05-10 09:01:28 33 15 0 36.25 0 0 0 1 1
30 2022-05-10 2022-05-10 09:01:29 0 0 0 0.00 0 0 0 1 0
I have the code to separate by date, and to "kinda" plot, but I need it for the 4 columns.
graph_pre <- mutate(graph_pre, day = lubridate::day(Date))
ggplot(graph_pre, aes(x = Time, y = Posture))
geom_point()
facet_wrap(~day, scales = "free_x")
dput(head(graph_pre,30))
structure(list(Date = structure(c(19122, 19122, 19122, 19122,
19122, 19122, 19122, 19122, 19122, 19122, 19122, 19122, 19122,
19122, 19122, 19122, 19122, 19122, 19122, 19122, 19122, 19122,
19122, 19122, 19122, 19122, 19122, 19122, 19122, 19122), class = "Date"),
Time = structure(c(1652187660, 1652187661, 1652187662, 1652187663,
1652187664, 1652187665, 1652187666, 1652187667, 1652187668,
1652187669, 1652187670, 1652187671, 1652187672, 1652187673,
1652187674, 1652187675, 1652187676, 1652187677, 1652187678,
1652187679, 1652187680, 1652187681, 1652187682, 1652187683,
1652187684, 1652187685, 1652187686, 1652187687, 1652187688,
1652187689), class = c("POSIXct", "POSIXt"), tzone = ""),
Axis1 = c(21, 0, 24, 48, 0, 0, 0, 0, 0, 20, 14, 11, 0, 0,
82, 60, 98, 151, 44, 6, 39, 17, 51, 15, 22, 114, 74, 117,
33, 0), Axis2 = c(40, 36, 1, 31, 6, 0, 0, 0, 5, 33, 26, 0,
0, 0, 126, 64, 140, 118, 13, 6, 8, 20, 46, 45, 34, 93, 67,
9, 15, 0), Axis3 = c(2, 1, 0, 4, 0, 0, 0, 0, 2, 3, 29, 4,
0, 0, 113, 47, 236, 221, 99, 53, 65, 57, 269, 82, 4, 41,
92, 40, 0, 0), VM = c(45.22, 36.01, 24.02, 57.28, 6, 0, 0,
0, 5.39, 38.7, 41.39, 11.7, 0, 0, 188.07, 99.52, 291.38,
292.52, 109.11, 53.67, 76.22, 62.75, 277.63, 94.73, 40.69,
152.73, 135.75, 123.98, 36.25, 0), Standing = c(0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), Stepping = c(0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0,
0, 0, 0, 0), Cycling = c(2, 0, 0, 2, 0, 0, 0, 0, 0, 0, 2,
0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 0, 0),
New_Sitting = c(0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1), Counter = c(0L,
1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L)), row.names = c(NA,
30L), class = "data.frame")
CodePudding user response：
First thing, we should pivot_longer to pull the four posture columns into name-value pairs. Here I've put the names into the "Posture" column. Then we can map that to color and use the values for the y axis.
I've specified the range in scale_y_continuous, but it could also be done with coord_cartesian(ylim = c(0.5,4.5)) -- the difference will be that the out of range points are filtered out in this way, but are in some sense "still there" if you use the coord_cartesian option. That can make a difference if you are doing a summary step, like geom_boxplot or geom_smooth.
Finally, I use theme to specify the y-axis related elements that should be hidden.
library(tidyverse)
graph %>%
mutate(day = lubridate::day(Date)) %>%
pivot_longer(Standing:New_Sitting, names_to = "Posture") %>%
ggplot(aes(x = Time, y = value, color = Posture))
geom_point()
scale_y_continuous(limits = c(0.5,4.5), expand = expansion(0))
facet_wrap(~day, scales = "free_x")
labs(title = "Posture vs. Time")
theme(axis.title.y = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank())
CodePudding user response：
Here you go:
library(tidyverse)
graph_pre_long <- graph_pre %>% pivot_longer(c(Standing, New_Sitting , Stepping, Cycling), names_to = "Posture")
ggplot(graph_pre_long, aes(x = Time, y = value, color = Posture))
geom_point()
facet_wrap(~day, scales = "free_x")
ylim(.5, 4.5)
theme(axis.title.y = element_blank(), axis.text.y = element_blank(), axis.ticks.y = element_blank())