问题
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/
回答1:
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.
来源:https://stackoverflow.com/questions/64869455/plot-multiple-time-series-lines-in-3d-with-ggplot-plotly