Related
I would like to plot both the raw data from df_plotting and the summary statistics from table_max (the mean values per conditon).
This is my code so far
Edit: Add apa <- c("#68246d", "#a53d55", "#b87246", "#afa961")
ggplot(table_max, mapping= aes(x = phase_bins, y = Mean)) +
geom_line(aes(group=as.numeric(cond_f),
colour = cond_f), size = 1.2)+
geom_line(df_plotting, mapping = aes(x=phase_bins, y = max_change_to_base,
group=interaction(ID, cond_f),
colour = cond_f, linetype =cond_f),
alpha = 0.3, size =0.3)+
geom_errorbar(table_max, mapping=aes(ymin=Mean-SD, ymax=Mean+SD, colour = cond_f),
width=.2, size = 0.7)+
facet_wrap(factor(sample, levels = c("UGi", "UKi", "UKa"))~.)+
labs(title="Max. temperature change by condition and sample", colour = "Condition:", linetype = "Condition:")+
theme(guides(linetype=guide_legend(override.aes = list(alpha = 1)))+
scale_x_discrete(labels=
c("base", "stim1", "stim2", "recovery", "break"), drop = T)+
scale_y_continuous(limits = c(-2,3))+
scale_colour_manual(name = "Condition:",
labels = c("artificial", "cry", "laugh", "babble"), values=apa) +
scale_linetype_manual(name = "Condition:",
labels = c("artificial", "cry", "laugh", "babble"),
values = c(1,2,3,4)) # also tried "solid", "dotted", "dashed", "twodashed"
The problem is, that this displays only solid lines for the legend, and I would like a combination of linetype and colour as one joint legend. I think this does not work because colour is assigned once to solid lines and then to the combination of linetype and colour and I can't override only one of the colour aesthetics.
Here is my data:
df_plotting
structure(list(ID = structure(c(35L, 35L, 35L, 35L, 35L), .Label = c("UG201",
"UG208", "UG209", "UG211", "UG215", "UG217", "UG219", "UG220",
"UG221", "UG222", "UG228", "UG243", "UG247", "UG254", "UG268",
"UG271", "UG272", "UG273", "UG274", "UG275", "UG280", "UG283",
"UG284", "UG286", "UG297", "UG299", "UG308", "UG310", "UG315",
"UG316", "UG330", "UG331", "UG334", "UG335", "UK103", "UK104",
"UK105", "UK106", "UK107", "UK108", "UK110", "UK111", "UK112",
"UK113", "UK115", "UK116", "UK117", "UK119", "UK122", "UK123",
"UK130", "UK132", "UK135", "UK136", "UK138", "UK139", "UK140",
"UK142", "UK145", "UK147", "UK150", "UK153", "UK155", "UK156",
"UK159", "UK160", "UK162", "UK164", "UKA102", "UKA103", "UKA104",
"UKA105", "UKA106", "UKA107", "UKA108", "UKA109", "UKA110", "UKA111",
"UKA112", "UKA113", "UKA114", "UKA115", "UKA116", "UKA117", "UKA119",
"UKA120", "UKA121", "UKA122"), class = "factor"), sex = structure(c(1L,
1L, 1L, 1L, 1L), .Label = c("f", "m"), class = "factor"), trial = structure(c(1L,
1L, 1L, 1L, 2L), .Label = c("1", "2", "3", "4"), class = "factor"),
cond_f = structure(c(3L, 3L, 3L, 3L, 2L), .Label = c("artificial",
"cry", "laugh", "babble"), class = "factor"), stimulus = structure(c(16L,
16L, 16L, 16L, 12L), .Label = c("a1", "a2", "a3", "a4", "b1",
"b2", "b3", "b4", "c1", "c2", "c3", "c4", "l1", "l2", "l3",
"l4"), class = "factor"), phase_bins = structure(c(2L, 3L,
4L, 5L, 2L), .Label = c("pre", "baseline", "stim_bin1", "stim_bin2",
"recovery", "break"), class = "factor"), mean_change_to_base = c(0,
-0.516666666666667, -0.0333333333333336, 0.433333333333333,
0), max_change_to_base = c(0, -0.933333333333334, 0.166666666666668,
0.566666666666666, 0), sample = structure(c(2L, 2L, 2L, 2L,
2L), .Label = c("UGi", "UKi", "UKa"), class = "factor")), row.names = c(NA,
-5L), groups = structure(list(ID = structure(c(35L, 35L), .Label = c("UG201",
"UG208", "UG209", "UG211", "UG215", "UG217", "UG219", "UG220",
"UG221", "UG222", "UG228", "UG243", "UG247", "UG254", "UG268",
"UG271", "UG272", "UG273", "UG274", "UG275", "UG280", "UG283",
"UG284", "UG286", "UG297", "UG299", "UG308", "UG310", "UG315",
"UG316", "UG330", "UG331", "UG334", "UG335", "UK103", "UK104",
"UK105", "UK106", "UK107", "UK108", "UK110", "UK111", "UK112",
"UK113", "UK115", "UK116", "UK117", "UK119", "UK122", "UK123",
"UK130", "UK132", "UK135", "UK136", "UK138", "UK139", "UK140",
"UK142", "UK145", "UK147", "UK150", "UK153", "UK155", "UK156",
"UK159", "UK160", "UK162", "UK164", "UKA102", "UKA103", "UKA104",
"UKA105", "UKA106", "UKA107", "UKA108", "UKA109", "UKA110", "UKA111",
"UKA112", "UKA113", "UKA114", "UKA115", "UKA116", "UKA117", "UKA119",
"UKA120", "UKA121", "UKA122"), class = "factor"), trial = structure(1:2, .Label = c("1",
"2", "3", "4"), class = "factor"), cond_f = structure(3:2, .Label = c("artificial",
"cry", "laugh", "babble"), class = "factor"), .rows = structure(list(
1:4, 5L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
table_max
structure(list(cond_f = structure(c(1L, 1L, 1L, 1L, 1L), .Label = c("artificial",
"cry", "laugh", "babble"), class = "factor"), phase_bins = structure(c(2L,
2L, 2L, 3L, 3L), .Label = c("pre", "baseline", "stim_bin1", "stim_bin2",
"recovery", "break"), class = "factor"), sample = structure(c(1L,
2L, 3L, 1L, 2L), .Label = c("UGi", "UKi", "UKa"), class = "factor"),
Mean = c(0, 0, 0, 0.244444444444444, 0.711111111111109),
SD = c(0, 0, 0, 0.760260897979524, 0.474268442504406), Min. = c(0,
0, 0, -0.899999999999999, 0.133333333333333), Max. = c(0,
0, 0, 1.8, 1.4), count = c(12L, 9L, 20L, 12L, 9L)), row.names = c(NA,
-5L), groups = structure(list(cond_f = structure(c(1L, 1L), .Label = c("artificial",
"cry", "laugh", "babble"), class = "factor"), phase_bins = structure(2:3, .Label = c("pre",
"baseline", "stim_bin1", "stim_bin2", "recovery", "break"), class = "factor"),
.rows = structure(list(1:3, 4:5), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
Thanks for any ideas on how to fix this!
The problem was in cond_f's factor levels. Note that I define both the vector of colors apa and the vector of line types lty. And assign names to each of these colors and line types from the factor cond_f levels.
First the plot without the scale_*'s.
library(ggplot2)
apa <- c("#68246d", "#a53d55", "#b87246", "#afa961")
apa <- setNames(apa, levels(df_plotting$cond_f))
lty <- c("solid", "dotted", "dashed", "twodash")
lty <- setNames(lty, levels(df_plotting$cond_f))
p <- ggplot(table_max, mapping= aes(x = phase_bins, y = Mean,
group = cond_f, colour = cond_f,
linetype = cond_f)) +
geom_line(size = 1.2) +
geom_line(
data = df_plotting,
mapping = aes(x = phase_bins, y = max_change_to_base,
group = interaction(ID, cond_f),
colour = cond_f,
linetype = cond_f),
alpha = 0.3, size = 0.3,
inherit.aes = FALSE
) +
geom_errorbar(
mapping = aes(ymin = Mean - SD, ymax = Mean + SD),
width = 0.2,
size = 0.7
)
Created on 2022-07-25 by the reprex package (v2.0.1)
Now the problem. The default drop = TRUE drops the unused factor levels, set it to FALSE on both scale_colour_manual and scale_linetype_manual.
p2 <- p +
scale_x_discrete(
labels = c("base", "stim1", "stim2", "recovery", "break"),
drop = TRUE
) +
scale_y_continuous(limits = c(-2, 3)) +
scale_colour_manual(
name = "Condition:",
labels = c("artificial", "cry", "laugh", "babble"),
values = apa,
drop = FALSE
) +
scale_linetype_manual(
name = "Condition:",
labels = c("artificial", "cry", "laugh", "babble"),
values = lty,
drop = FALSE
) +
labs(
title = "Max. temperature change by condition and sample",
colour = "Condition:",
linetype = "Condition:"
) +
facet_wrap(sample ~ .)
p2
#> geom_path: Each group consists of only one observation. Do you need to adjust
#> the group aesthetic?
Created on 2022-07-25 by the reprex package (v2.0.1)
I don't believe this makes a difference.
p2 + guides(linetype = guide_legend(override.aes = list(alpha = 1)))
I am having difficulty customising the ggplot (geom_point) output.
Points to have black outline but with different fill colors by group (white and black)
Is there a way to combine the legend into one?
Data
library(dplyr)
library(ggplot2)
dat <- structure(list(q = c(1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 5L, 5L),
is_female = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L), levels = c("Male", "Female"), class = "factor"), mean_exp = c(19.3095475534936,
19.2351713991988, 21.6718804471611, 21.69517120871, 23.4144749290445,
23.4191383190372, 25.2817658487443, 25.2772340355605, 28.3982168611512,
28.7869521340185), mean_fi = c(0.0915386254018914, 0.0912295567094683,
0.0771055282779973, 0.0790597510143077, 0.0859508568981647,
0.088489590940481, 0.109848283385112, 0.11358904634185, 0.128425331060705,
0.136830729164909), b_fi.frail = c(1, 1, 1, 1, 1, 1, 1, 1,
1, 1), pct = c(47.5830407777478, 52.4169592222522, 37.567084078712,
62.432915921288, 36.9897959183673, 63.0102040816327, 34.0960360941025,
65.9039639058975, 29.0891283055828, 70.9108716944172)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -10L), groups = structure(list(
q = 1:5, .rows = structure(list(1:2, 3:4, 5:6, 7:8, 9:10), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -5L), .drop = TRUE))
My attempt:
ggplot(dat, aes(x=mean_exp, y=mean_fi, linetype=is_female)) +
geom_point(aes(color=is_female, fill=is_female), size=2, shape="square") +
geom_line() +
scale_x_continuous(limits = c(18, 30), breaks = seq(20, 30, 5), expand = c(0,0)) +
scale_y_continuous(limits = c(0.05, 0.15), breaks = seq(0.05, 0.15, 0.02), expand = c(0,0)) +
scale_color_manual(values = c("M" = "black", "F" = "black")) +
scale_fill_manual(values = c("M" = "black", "F" = "white")) +
labs(x= expression(Body ~ mass ~ index ~ (kg/m^2)), y= "Mean baseline FI score", title = "BMI") +
theme_classic() +
theme(plot.title = element_text(hjust=0.5),
legend.position = "bottom")
My code outputs a graph with grey points and lines for some reason. I would like black lines and outlines (but points to be filled with black or white depending on the group) and to combine the legend if possible.
I realise there are many similar examples out there but I can't seem to figure out why my code is not working... Thanks for your help in advance!
Use shape = 22 for a fillable square, i.e. one which can have a different outline.
Colour can be outside the aes if both groups require a black outline for the points.
library(dplyr)
library(ggplot2)
dat <- structure(list(
q = c(1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 5L, 5L),
is_female = structure(c(
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L
), levels = c("Male", "Female"), class = "factor"), mean_exp = c(
19.3095475534936,
19.2351713991988, 21.6718804471611, 21.69517120871, 23.4144749290445,
23.4191383190372, 25.2817658487443, 25.2772340355605, 28.3982168611512,
28.7869521340185
), mean_fi = c(
0.0915386254018914, 0.0912295567094683,
0.0771055282779973, 0.0790597510143077, 0.0859508568981647,
0.088489590940481, 0.109848283385112, 0.11358904634185, 0.128425331060705,
0.136830729164909
), b_fi.frail = c(
1, 1, 1, 1, 1, 1, 1, 1,
1, 1
), pct = c(
47.5830407777478, 52.4169592222522, 37.567084078712,
62.432915921288, 36.9897959183673, 63.0102040816327, 34.0960360941025,
65.9039639058975, 29.0891283055828, 70.9108716944172
)
), class = c(
"grouped_df",
"tbl_df", "tbl", "data.frame"
), row.names = c(NA, -10L), groups = structure(list(
q = 1:5, .rows = structure(list(1:2, 3:4, 5:6, 7:8, 9:10), ptype = integer(0), class = c(
"vctrs_list_of",
"vctrs_vctr", "list"
))
), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -5L), .drop = TRUE))
ggplot(dat, aes(x = mean_exp, y = mean_fi, linetype = is_female)) +
geom_point(aes(fill = is_female), size = 2, shape = 22, colour = "black") +
geom_line() +
scale_x_continuous(limits = c(18, 30), breaks = seq(20, 30, 5), expand = c(0, 0)) +
scale_y_continuous(limits = c(0.05, 0.15), breaks = seq(0.05, 0.15, 0.02), expand = c(0, 0)) +
scale_fill_manual(values = c("black", "white")) +
labs(x = expression(Body ~ mass ~ index ~ (kg / m^2)), y = "Mean baseline FI score",
title = "BMI", fill = "Sex", linetype = "Sex") +
theme_classic() +
theme(
plot.title = element_text(hjust = 0.5),
legend.position = "bottom"
)
Created on 2022-07-07 by the reprex package (v2.0.1)
I would like create a plot like this:
i.e. i would like to add another bar plot inside in my bar plot basic,
whould could i do something like this ?
i have no idea about how create this,
data:
structure(list(Impacted_sector = structure(c(3L, 3L, 1L, 1L,
5L, 2L, 4L), .Label = c("Authorities-Stakeholders", "Public and social welfare",
"Agriculture", "Variety", "Environment"), class = "factor", scores = structure(c(Agriculture = -4.49129192,
`Authorities-Stakeholders` = -3125.027684115, Environment = -0.33176146,
`Public and social welfare` = -15.46511976, Variety = -0.39712811
), .Dim = 5L, .Dimnames = list(c("Agriculture", "Authorities-Stakeholders",
"Environment", "Public and social welfare", "Variety")))), Type_of_cost_merged = structure(c(2L,
1L, 1L, 3L, 1L, 2L, 1L), .Label = c("Management", "Damage", "Mixed"
), class = "factor", scores = structure(c(Damage = -7.803309445,
Management = -1564.7958562425, Mixed = -0.44191754), .Dim = 3L, .Dimnames = list(
c("Damage", "Management", "Mixed")))), cost = c(141499.13,
8841084.71, 6249613450.69, 441917.54, 331761.46, 15465119.76,
397128.11), Million = c(0.14149913, 8.84108471, 6249.61345069,
0.44191754, 0.33176146, 15.46511976, 0.39712811)), row.names = c(NA,
-7L), groups = structure(list(Impacted_sector = structure(1:5, .Label = c("Authorities-Stakeholders",
"Public and social welfare", "Agriculture", "Variety", "Environment"
), scores = structure(c(Agriculture = -4.49129192, `Authorities-Stakeholders` = -3125.027684115,
Environment = -0.33176146, `Public and social welfare` = -15.46511976,
Variety = -0.39712811), .Dim = 5L, .Dimnames = list(c("Agriculture",
"Authorities-Stakeholders", "Environment", "Public and social welfare",
"Variety"))), class = "factor"), .rows = structure(list(3:4,
6L, 1:2, 7L, 5L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -5L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
All help is appreciate
As I mentioned in my comment one option would be to make use of patchwork::inset_element. As in your data the cost for Authorities-Stakeholders differs heavily from the cost of the other categories I opted for adding Authorities-Stakeholders as an inset plot.
library(ggplot2)
library(patchwork)
library(dplyr)
p1 <- dd %>%
filter(!Impacted_sector == "Authorities-Stakeholders") %>%
ggplot(aes(Impacted_sector, cost, fill = Type_of_cost_merged)) +
geom_col() +
scale_y_continuous(labels = scales::number_format(scale = 1e-6), expand = c(0, .05)) +
theme_minimal() +
guides(fill = guide_legend(override.aes = list(color = "black"))) +
labs(fill = "Type of cost")
p2 <- dd %>%
filter(Impacted_sector == "Authorities-Stakeholders") %>%
ggplot(aes(Impacted_sector, cost, fill = Type_of_cost_merged)) +
geom_col() +
scale_y_continuous(labels = scales::number_format(scale = 1e-6), expand = c(0, .05)) +
theme_minimal() +
theme(plot.background = element_rect(fill = "white", color = NA)) +
guides(fill = "none") +
labs(x = NULL, y = NULL)
p1 + patchwork::inset_element(p2, .6, .6, 1, 1)
I am trying to make an animated cumulative map plot of the following data:
structure(list(station_install_date = structure(c(16684, 16684,
16684, 16684, 16684, 16684), class = "Date"), lat = c(37.548645,
37.549561, 37.550007, 37.550629, 37.552746, 37.554951), long = c(126.912827,
126.905754, 126.914825, 126.914986, 126.918617, 126.910835),
capa_sum = c(10L, 5L, 5L, 13L, 10L, 14L)), row.names = c(NA,
-6L), groups = structure(list(station_install_date = structure(c(16684,
16684, 16684, 16684, 16684, 16684), class = "Date"), lat = c(37.548645,
37.549561, 37.550007, 37.550629, 37.552746, 37.554951), .rows = structure(list(
1L, 2L, 3L, 4L, 5L, 6L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
My code looks as below:
seoul <- get_googlemap("Seoul, South Korea", zoom=11, maptype = "roadmap")
ggmap(seoul) +
geom_point(data = install_time_df, aes(x = long, y = lat), color = "red", alpha = 0.3) +
transition_time(station_install_date) +
ease_aes("linear")
However, I keep getting the error:
Error in seq.default(range[1], range[2], length.out = nframes) :
'from' must be a finite number
Try:
p2<- ggmap(seoul) +
geom_point(data = install_time_df, aes(x = long, y = lat), color = "red", alpha = 0.3) +
transition_manual(station_install_date, cumulative = TRUE) +
ease_aes("linear")
anim2<- animate(p2, renderer = gifski_renderer())
anim_save("C:\\Users\\82104\\Desktop\\따릉이\\anim2.gif", animation = anim2)
Closed. This question is not reproducible or was caused by typos. It is not currently accepting answers.
This question was caused by a typo or a problem that can no longer be reproduced. While similar questions may be on-topic here, this one was resolved in a way less likely to help future readers.
Closed 2 years ago.
Improve this question
I have the following dataset showing when a person (denoted by variable id) synced data to the server in districts A and B. I already computed counts and percentages by district and year.
This is my summarized data:
df3 <- structure(list(district = c("A", "A", "B", "B"), year_sync = c(
2019L,
2020L, 2019L, 2020L
), ssum = c(32L, 32L, 33L, 33L), n = c(
7L,
25L, 25L, 8L
), percent = c(
0.21875, 0.78125, 0.757575757575758,
0.242424242424242
), label = c("21.88%", "78.12%", "75.76%", "24.24%")), row.names = c(NA, -4L), groups = structure(list(district = c(
"A",
"B"
), .rows = structure(list(1:2, 3:4), ptype = integer(0), class = c(
"vctrs_list_of",
"vctrs_vctr", "list"
))), row.names = 1:2, class = c(
"tbl_df",
"tbl", "data.frame"
), .drop = TRUE), class = c(
"grouped_df",
"tbl_df", "tbl", "data.frame"
))
I need to create a ggplot (like the one shown below).
This is my plotting code:
ggplot(df3, aes(y=ssum, x=factor(year_sync), fill=district)) +
geom_bar(stat='identity',
#color='black',
position = position_dodge(width=0.8), width=0.8) +
geom_text(aes(label = label),
position = position_dodge(width=0.8),
size = 3) +
xlab ("Year") +
ylab ("Number of People") +
scale_fill_manual(values=c("aquamarine4", "bisque3")) +
theme_minimal() +
theme(plot.title = element_text(hjust = 0.5, face = "bold"),
plot.subtitle = element_text(hjust = 0.5, face = "italic"))
However, the second part of the code gives me the following error: Error in unique.default(x, nmax = nmax) : unique() applies only to vectors.
Can anyone please help in telling what am I doing wrong as I am new to R.
Looking forward to solving this!
Thank you
Simply replacing year with year_sync, countby n and mapping n on the y aes (instead of ssum) gives the wanted plot without any error messages:
df3 <- structure(list(district = c("A", "A", "B", "B"), year_sync = c(
2019L,
2020L, 2019L, 2020L
), ssum = c(32L, 32L, 33L, 33L), n = c(
7L,
25L, 25L, 8L
), percent = c(
0.21875, 0.78125, 0.757575757575758,
0.242424242424242
), label = c("21.88%", "78.12%", "75.76%", "24.24%")), row.names = c(NA, -4L), groups = structure(list(district = c(
"A",
"B"
), .rows = structure(list(1:2, 3:4), ptype = integer(0), class = c(
"vctrs_list_of",
"vctrs_vctr", "list"
))), row.names = 1:2, class = c(
"tbl_df",
"tbl", "data.frame"
), .drop = TRUE), class = c(
"grouped_df",
"tbl_df", "tbl", "data.frame"
))
library(ggplot2)
ggplot(df3, aes(y = n, x = factor(year_sync), fill = district)) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge(width = 0.8), width = 0.8
) +
geom_text(aes(label = label, y = n),
position = position_dodge(width = 0.8),
size = 3, vjust = -1
) +
xlab("Year") +
ylab("Number of People") +
scale_fill_manual(values = c("aquamarine4", "bisque3")) +
theme_minimal() +
theme(
plot.title = element_text(hjust = 0.5, face = "bold"),
plot.subtitle = element_text(hjust = 0.5, face = "italic")
)