英文:
Custom heatmap theme in R?
问题
I understand that you're looking for a translation of the content you provided without the code. Here's the translated text:
以下是要翻译的内容：
下面显示的图表中使用了什么主题，或者可以使用什么类似的主题来创建一个吸引人的图表，就像提供的照片中的那个一样？我在互联网上看到了这张照片，但没有提供代码。我已经找到了代码，但目前的主题难以解释。
如上所示，每个“周”和“年龄”组合都有一个单独的方框。非常容易看出某个年龄组在特定周的COVID数字是多少。有人可以告诉我以下主题是什么，或者建议一个类似的主题来改进图表的外观，以适应科学观众吗？
这是我的数据的可重现示例：
在我的图表中，对于“mean_temp” [17.17, 17.6] 和“total_count” [0, 14.5] 的组合，应该有一个单独的方框，其中“total_count”为53.5。具有值的单元格已合并，因此难以解释。我不希望个别方框重叠。每个单元格中有多个观察结果。假设对于“mean_temp”的一个特定范围，与“total_count”的一个范围相结合，我有值5、15、100，所以我必须使用平均数。感谢任何帮助。
英文:
What is the theme used in the graph shown below, or what similar theme can be used to create an appealing graph like the one in the provided photo? I saw the photo on the internet but no code was given. I have already sourced the code, but it's hard to interpret with the current theme.
As shown above, There is a separate box for each week and age combination. It is very easy to tell what were covid number in a particular week for a certain age group. Can someone tell what's the following theme, or suggest a similar theme to improve the graph's appearance for scientific audience?
Here is the reproducible example of my data
df <- structure(
list(
total_count = c(
10L,
0L,
15L,
0L,
20L,
0L,
0L,
50L,
0L,
6L,
1L,
10L,
7L,
0L,
0L,
29L,
0L,
2L,
11L,
3L,
0L,
12L,
0L,
30L,
0L,
0L,
29L,
44L,
10L,
5L,
2L,
145L,
0L,
70L
),
mean_temp = c(
18.87,
18.87,
18.87,
18.87,
18.87,
18.87,
18.87,
18.87,
18.87,
21.85,
21.85,
21.85,
21.85,
21.85,
21.85,
21.85,
21.85,
21.85,
17.11,
17.11,
17.11,
17.11,
17.11,
17.11,
17.11,
17.11,
18.82,
18.82,
18.82,
18.82,
18.82,
18.82,
18.82,
18.82
),
lwd_duration = c(
64.32,
64.32,
64.32,
64.32,
64.32,
64.32,
64.32,
64.32,
64.32,
104.2,
104.2,
104.2,
104.2,
104.2,
104.2,
104.2,
104.2,
104.2,
53.53,
53.53,
53.53,
53.53,
53.53,
53.53,
53.53,
53.53,
60.43,
60.43,
60.43,
60.43,
60.43,
60.43,
60.43,
60.43
)
),
row.names = c(NA,-34L),
class = c("tbl_df", "tbl", "data.frame"),
na.action = structure(
c(
`4` = 4L,
`5` = 5L,
`6` = 6L,
`7` = 7L,
`8` = 8L,
`9` = 9L,
`78` = 78L,
`87` = 87L,
`96` = 96L,
`105` = 105L,
`114` = 114L,
`123` = 123L,
`132` = 132L,
`141` = 141L,
`150` = 150L,
`159` = 159L,
`168` = 168L,
`177` = 177L,
`186` = 186L,
`849` = 849L,
`850` = 850L,
`851` = 851L,
`852` = 852L,
`891` = 891L,
`892` = 892L,
`893` = 893L,
`894` = 894L,
`921` = 921L,
`922` = 922L,
`923` = 923L,
`924` = 924L,
`937` = 937L,
`938` = 938L,
`939` = 939L,
`940` = 940L,
`969` = 969L,
`970` = 970L,
`971` = 971L,
`972` = 972L,
`985` = 985L,
`986` = 986L,
`987` = 987L,
`988` = 988L,
`1017` = 1017L,
`1018` = 1018L,
`1019` = 1019L,
`1020` = 1020L,
`1033` = 1033L,
`1034` = 1034L,
`1035` = 1035L,
`1036` = 1036L
),
class = "omit"
)
)
Code used to produce the figure:
dat2 <-
df %>%
as_tibble() %>%
mutate(
mean_temp = cut_interval(mean_temp, n = 10),
total_count = cut_interval(total_count, n = 10),
) %>%
group_by(mean_temp, total_count) %>%
summarize(lwd_duration = mean(lwd_duration))
#> `summarise()` has grouped output by 'mean_temp'. You can override using the
#> `.groups` argument.
ggplot(dat2, aes(mean_temp, total_count)) +
geom_tile(aes(fill = lwd_duration)) +
geom_text(aes(label = round(lwd_duration, 1))) +
scale_fill_gradient(low = "white", high = "red")
In my graph, I should have a separate box for the mean_temp [17.17, 17.6] and total_count [0, 14.5] combination with total_count 53.5 inside the box. Cells with values have merged, so it's hard to interpret. I don't want individual boxes overlapping. I have multiple observations in each cell. Suppose for one particular range of mean_temp combined with one range of total_count, I have values 5, 15, 100, so I had to use mean numbers. Thanks for any assistance.
答案1
得分: 0
以下是您要翻译的代码部分：
library(ggplot2)
library(dplyr)
df %>%
mutate(
mean_temp = cut_interval(mean_temp, n = 10),
total_count = cut_interval(total_count, n = 10),
) %>%
group_by(mean_temp, total_count) %>%
summarize(lwd_duration = mean(lwd_duration)) %>%
ggplot(aes(mean_temp, total_count, fill = lwd_duration)) +
geom_tile(color = 'white', linewidth = 1.5) +
geom_text(aes(label = round(lwd_duration, 1))) +
scale_fill_gradient(low = "white", high = "red") +
theme(panel.grid.major = element_blank(),
panel.background = element_rect(fill = 'white'))
请注意，这是R编程语言中的一段代码，用于创建可视化图表。
英文:
library(ggplot2)
library(dplyr)
df %>%
mutate(
mean_temp = cut_interval(mean_temp, n = 10),
total_count = cut_interval(total_count, n = 10),
) %>%
group_by(mean_temp, total_count) %>%
summarize(lwd_duration = mean(lwd_duration)) %>%
ggplot(aes(mean_temp, total_count, fill = lwd_duration)) +
geom_tile(color = 'white', linewidth = 1.5) +
geom_text(aes(label = round(lwd_duration, 1))) +
scale_fill_gradient(low = "white", high = "red") +
theme(panel.grid.major = element_blank(),
panel.background = element_rect(fill = 'white'))
#> `summarise()` has grouped output by 'mean_temp'. You can override using the
#> `.groups` argument.
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<sup>Created on 2023-04-19 with reprex v2.0.2</sup>
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