使用ggplot/plotly在3D中绘制多条时序线 [英] Plot multiple time-series lines in 3D with ggplot/plotly

问题描述

我有一个数据帧，其中包含我要尝试以3D方式绘制的不同时间序列信号，其中x轴表示时间，Y轴表示所有线的标准值，Z轴显示每一行.这是我的意思的例子.

我有一段代码，我现在尝试配置以正确输出，但是我不确定如何正确分配y和z变量.df包含5列；时间+ 4种不同的时间序列信号.

  plot_ly(数据= dfx = df $ Time，y =标度(df)，z =名称(df)，类型='scatter3d'，模式='线'，颜色= c('红色'，'蓝色'，'黄色'，'绿色')) 

数据框如下所示:

 时间coup.nu Coup.nuti coup.Ca coup.B1 198.001 0.0002630826 0.0003027965 2.141347e-07 12 198.002 0.0002630829 0.0003027953 2.141379e-07 13 198.003 0.0002630833 0.0003027940 2.141412e-07 14 198.004 0.0002630836 0.0003027928 2.141444e-07 15 198.005 0.0002630840 0.0003027916 2.141477e-07 1 

我正在尝试使用plotly或ggplot执行渲染.感谢您的帮助！

我从以下来源获得此资源:

如果要避免重塑 data.frame ，可以使用 add_trace 为数据的每一列添加新的跟踪.

I have a data frame containing different time-series signals which I'm trying to plot in 3D, with the x-axis representing Time, the Y-axis representing a standardized value for all the lines, and the Z-axis showing each line. Here's an example of what I mean.

I have a snippet of code I'm trying to configure now to output it properly but I'm not sure how to properly assign the y and z variables. The df contains 5 columns; Time + 4 different time-series signals.

plot_ly(
  data = df,
  x = df$Time,
  y = scale(df),
  z = names(df),
  type = 'scatter3d',
  mode = 'lines',
  color = c('red', 'blue', 'yellow', 'green'))

Dataframe looks like so:

      Time       coup.nu          Coup.nuti       coup.Ca       coup.B
1  198.001  0.0002630826       0.0003027965  2.141347e-07            1
2  198.002  0.0002630829       0.0003027953  2.141379e-07            1
3  198.003  0.0002630833       0.0003027940  2.141412e-07            1
4  198.004  0.0002630836       0.0003027928  2.141444e-07            1
5  198.005  0.0002630840       0.0003027916  2.141477e-07            1

I'm trying to use plotly or ggplot to perform the render. Thanks for the help!

I sourced this from: https://www.r-bloggers.com/2016/06/3d-density-plot-in-r-with-plotly/

解决方案

In a case like this you should reformat your data from wide to long using e.g. melt:

library(plotly)
library(reshape2)

DF <- data.frame(
        Time = c(198.001, 198.002, 198.003, 198.004, 198.005),
     coup.nu = c(0.000263083,0.000263083,0.000263083, 0.000263084,0.000263084),
   Coup.nuti = c(0.000302797,0.000302795,0.000302794, 0.000302793,0.000302792),
     coup.Ca = c(2.14e-07, 2.14e-07, 2.14e-07, 2.14e-07, 2.14e-07),
      coup.B = c(1L, 1L, 1L, 1L, 1L)
)
DF_long <- melt(DF, id.vars=c("Time"))

plot_ly(
  data = DF_long,
  type = 'scatter3d',
  mode = 'lines',
  x = ~ Time,
  y = ~ value,
  z = ~ variable,
  color = ~ variable,
  colors = c('red', 'blue', 'yellow', 'green'))

If you want to avoid reshaping your data.frame you could use add_trace to add a new trace for each column of your data.

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