Às 14:24 de 12/05/2023, Kevin Zembower via R-help escreveu:
Hello, I'm trying to create a line graph with a legend, but have no
success controlling the legend. Since nothing I've tried seems to work,
I must be doing something systematically wrong. Can anyone point this
out to me?
Here's my data:
> weights
# A tibble: 1,246 × 3
Date J K
<date> <dbl> <dbl>
1 2000-02-13 133 188
2 2000-02-20 134 185
3 2000-02-27 135 187
4 2000-03-05 135 185
5 2000-03-12 NA 184
6 2000-03-19 NA 184.
7 2000-03-26 136 184.
8 2000-04-02 134 185
9 2000-04-09 133 186
10 2000-04-16 NA 186
# ℹ 1,236 more rows
# ℹ Use `print(n = ...)` to see more rows
>
Here's my attempts. You can see some of the things I've tried in the
commented out sections:
weights %>%
group_by(year(Date)) %>%
summarize(
m_K = mean(K, na.rm = TRUE),
m_J = mean(J, na.rm = TRUE),
) %>%
ggplot(aes(x = `year(Date)`)) +
geom_point(aes(y = m_K, color = "red")) +
geom_smooth(aes(y = m_K, color = "red")) +
geom_point(aes(y = m_J, color = "blue")) +
geom_smooth(aes(y = m_J, color = "blue")) +
guides(size = "legend",
shape = "legend")
## scale_shape_discrete(name="Person",
## breaks=c("m_K", "m_J"),
## labels=c("K", "J"))
## theme(legend.title=element_blank())
When this runs, the blue line for "K" is above the red line for "J", as
I expect, but in the legend, the red is shown first, and labeled "blue."
I'd like to be able to create a legend where the first entry shows a
blue line and is labeled "K" and the second is red and labeled "J".
On a different but related topic, I'd welcome any advice or suggestions
on my methodology in this example. Is this the correct way to summarize
with a mean? Do I need the two sets of geom_point and geom_line clauses
to create this graph, or is there a better way?
Thanks for all your advice and guidance.
-Kevin
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Hello,
This is mainly a data reshaping problem. Insteadof plotting two
variables, J and K, if the data is in the long format you will map the
column with these variables names to the color aesthetic and call each
geom_* only once. Then, assign the colors you want.
As for placing K above J, note that ggplot places them by alphabetical
order unless you coerce to factor with the levels in the order you want.
Also, if you want to compute aggregate statistics for several columns,
use ?across. See the code below.
Here is a complete example. I have augmented your data set in order to
have more years to plot.
# augment the data set
weights <- " Date J K
1 2000-02-13 133 188
2 2000-02-20 134 185
3 2000-02-27 135 187
4 2000-03-05 135 185
5 2000-03-12 NA 184
6 2000-03-19 NA 184.
7 2000-03-26 136 184.
8 2000-04-02 134 185
9 2000-04-09 133 186
10 2000-04-16 NA 186"
weights <- read.table(text = weights, header = TRUE)
weights$Date <- as.Date(weights$Date)
tmp <- weights
tmp <- lapply(1:10, \(y) {
tmp$Date <- years(y) + tmp$Date
tmp$J <- tmp$J + sample(-10:10, nrow(weights), TRUE)
tmp$K <- tmp$K + sample(-10:10, nrow(weights), TRUE)
tmp
})
weights <- do.call(rbind, tmp)
#---
# plot code
library(ggplot2)
library(dplyr)
library(tidyr)
library(lubridate)
weights %>%
mutate(Year = year(Date)) %>%
group_by(Year) %>%
summarize(across(J:K, mean, na.rm = TRUE)) %>%
# now reshape the data
pivot_longer(-Year) %>%
# uncomment the next line if you want K
# to show up on top in the legend
# mutate(name = factor(name, levels = c("K", "J"))) %>%
ggplot(aes(Year, value, color = name)) +
geom_smooth(
formula = y ~ x,
method = lm,
se = FALSE
) +
geom_point() +
scale_color_manual(values = c(J = "red", K = "blue"))
Hope this helps,
Rui Barradas
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