R:在图表之间切换 [英] R: Switching Between Graphs
问题描述
我正在使用 R 编程语言.我正在尝试按照此处关于在图表之间切换"的教程进行操作.:
还添加箱形图
为不同类型的图(如箱线图)添加选项有点困难.现在的问题是箱线图中的 x 轴和散点图中的 x 轴是不同的.所以你不能使用相同的轴.幸运的是，plotly 允许您将不同的轨迹映射到不同的轴.然后，您可以使用 domain 属性设置这个新轴在完整图中的位置.
我的解决方案有点老套，因为我使用 domain 属性来隐藏".情节"我不想通过让它变得非常小来使用(我还通过设置 visible = FALSE 使相应的数据不可见).这是因为隐藏轴只会隐藏线条.剧情的背景还剩下你.
请注意，现在我使用方法 update(而不是 restyle)，因为它还允许您更改绘图的布局(
I am using the R programming language. I am trying to follow the tutorial here on "switching between graphs" : https://plotly.com/r/dropdowns/ (first example).
First, I generated some data in R:
library(plotly)
library(MASS)
x <- sample( LETTERS[1:4], 1000, replace=TRUE, prob=c(0.25, 0.25, 0.25, 0.25) )
y <- rnorm(1000,10,10)
z <- rnorm(1000,5,5)
df <- data.frame(x,y, z)
df$x = as.factor(df$x)
colnames(df) <- c("x", "y", "z")
I tried to modify the code from this tutorial to make the final result:
fig <- plot_ly(df, x = ~x, y = ~y, z = ~z alpha = 0.3)
fig <- fig %>% add_markers(marker = list(line = list(color = "black", width = 1)))
fig <- fig %>% layout(
title = "Drop down menus - Plot type",
xaxis = list(domain = c(0.1, 1)),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.8,
buttons = list(
list(method = "restyle",
args = list("type", "scatter"),
label = "Scatter A"),
list(method = "restyle",
args = list("type", "scatter"),
label = "Scatter B"),
list(method = "restyle",
args = list("type", "scatter"),
label = "Scatter C"),
list(method = "restyle",
args = list("type", "scatter"),
label = "Scatter D")
))
But this does not seem to be working.
Instead, I had a different idea: Perhaps I could create a series of graphs that I want to be able to "switch" between:
df_1 <- df[which(df$x == "A"),]
df_2 <- df[which(df$x == "B"),]
df_3 <- df[which(df$x == "C"),]
df_4 <- df[which(df$x == "D"),]
graph_1 <- plot_ly( data = df_1, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 1")
graph_2 <- plot_ly( data = df_2, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 2")
graph_3 <- plot_ly( data = df_3, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 3")
graph_4 <- plot_ly( data = df_4, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 4")
graph_5 <- plot_ly(df, y = ~y, color = ~x, type = "box") %>% layout(title = "boxplot")
Now, is it possible to modify the plotly code to "tie" all these graphs (graph_1, graph_2, graph_3, graph_4, graph_5) together, so that the user can click the tab on the left and switch between these graphs?
Thanks
The example you should look at the tutorial is the last one (with the sine waves). It hides and shows different traces of the plot depending on the value of the selection in the dropdown menu.
You just need to change the format of your dataframe to wide.
df.wide <- df %>% tidyr::pivot_wider(names_from = x, values_from=z)
df.wide
## A tibble: 1,000 x 5
# y D B A C
# <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 6.48 6.21 NA NA NA
# 2 23.6 NA 15.3 NA NA
# 3 -9.99 -2.16 NA NA NA
# 4 19.6 NA NA 0.0683 NA
# 5 18.8 -1.40 NA NA NA
# 6 -2.71 9.80 NA NA NA
# 7 2.32 NA NA NA 3.77
# 8 11.9 NA 4.35 NA NA
# 9 21.4 NA NA NA 13.9
#10 2.34 NA 2.10 NA NA
## … with 990 more rows
Then add a separate scatter trace for each column. In the arguments of the dropdown menu you can set which traces are going to be visible when each option is selected. For example args = list("visible", list(TRUE, FALSE, FALSE, FALSE)) means that only the first trace added (in this case column A) is going to be visible.
fig <- plot_ly(df.wide, x = ~y)
fig <- fig %>%
add_trace(y = ~A, name = "A", type='scatter', mode='markers') %>%
add_trace(y = ~B, name = "B", type='scatter', mode='markers', visible = F) %>%
add_trace(y = ~C, name = "C", type='scatter', mode='markers', visible = F) %>%
add_trace(y = ~D, name = "D", type='scatter', mode='markers', visible = F) %>%
layout(xaxis = list(domain = c(0.1, 1)),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
buttons = list(
list(method = "restyle",
args = list("visible", list(TRUE, FALSE, FALSE, FALSE)),
label = "A"),
list(method = "restyle",
args = list("visible", list(FALSE, TRUE, FALSE, FALSE)),
label = "B"),
list(method = "restyle",
args = list("visible", list(FALSE, FALSE, TRUE, FALSE)),
label = "C"),
list(method = "restyle",
args = list("visible", list(FALSE, FALSE, FALSE, TRUE)),
label = "D")))))
EDIT: Adding also a box plot
Adding an option for a different type of plot (like a box plot) is a little bit harder. The issue now is that x axis in the box plot and scatter plot are different. So you can't use the same axis. Fortunately, plotly lets you map different traces to different axis. Then you can set the position of this new axis within the complete plot using the domain attribute.
My solution is a little bit hacky because I used the domain attribute to "hide" the "plot" I did not want to use by making it very small (I also made the corresponding data invisible by setting visible = FALSE). This is because hiding the axis only hides the lines. You are still left with the background of the plot.
Note that now I use the method update (instead of restyle) because it allows you to change also the layout of the plot (https://plotly.com/r/custom-buttons/).
But it seemed to work very well!
# I had to reorder the dataframe because the boxplot was not following the order of the factors. Apparently it follows the orders that the letter appear.
df <- df %>% dplyr::arrange(x)
df.wide <- df %>% tidyr::pivot_wider(names_from = x, values_from=z)
# this is a list with axis config for scatter plot (define here to avoid repetition)
axis.config.scatter <- list(xaxis = list(title = "x", domain = c(0.1, 1), visible=T),
yaxis = list(title = "y", domain = c(0, 1), visible=T),
xaxis2 = list(title = "group", domain = c(0.99, 1), visible=F),
yaxis2 = list(title = "y", domain = c(0,99, 1), visible=F))
# this is a list with axis config for box plot (define here to avoid repetition)
axis.config.box <- list(xaxis = list(title = "x", domain = c(0.99, 1), visible=F),
yaxis = list(title = "y", domain = c(0.99, 1), visible=F),
xaxis2 = list(title = "group", domain = c(0.1, 1), visible=T, anchor='free'),
yaxis2 = list(title = "y", domain = c(0, 1), visible=T, anchor='free'))
fig <- plot_ly(df.wide)
fig <- fig %>%
add_trace(x = ~y, y = ~A, name = "A", type='scatter', mode='markers') %>%
add_trace(x = ~y, y = ~B, name = "B", type='scatter', mode='markers', visible = F) %>%
add_trace(x = ~y, y = ~C, name = "C", type='scatter', mode='markers', visible = F) %>%
add_trace(x = ~y, y = ~D, name = "D", type='scatter', mode='markers', visible = F) %>%
add_trace(data=df, x=~x, y=~z, name='box', type='box', visible=F, xaxis='x2', yaxis='y2') %>%
layout(xaxis = list(title = "x", domain = c(0.1, 1)),
yaxis = list(title = "y"),
xaxis2 = list(title = "group", domain = c(0.99, 1), visible=F),
yaxis2 = list(title = "y", domain = c(0.99, 1), visible=F),
updatemenus = list(
list(
y = 0.7,
buttons = list(
list(method = "update",
args = list(list(visible = c(TRUE, FALSE, FALSE, FALSE, FALSE)),
axis.config.scatter),
label = "A"),
list(method = "update",
args = list(list(visible = c(FALSE, TRUE, FALSE, FALSE, FALSE)),
axis.config.scatter),
label = "B"),
list(method = "update",
args = list(list(visible = c(FALSE, FALSE, TRUE, FALSE, FALSE)),
axis.config.scatter),
label = "C"),
list(method = "update",
args = list(list(visible = c(FALSE, FALSE, FALSE, TRUE, FALSE)),
axis.config.scatter),
label = "D"),
list(method = "update",
args = list(list(visible = c(FALSE, FALSE, FALSE, FALSE, TRUE)),
axis.config.box),
label = "box")
))))
这篇关于R:在图表之间切换的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
