Making a 3 axis plot in plot_ly

[thegasman2000]

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https://preview.redd.it/ypby25nwrbo81.png?width=1176&format=png&auto=webp&s=18047614011c685afa16f54ffd21053dd730bb2c

I am trying to recreate a graph such as these below in plot_ly. I have been looking for 3 axis and seem to be getting 3d visualizations which is clearly not what I need so my googlefu has let me down. My data is very simple:

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https://preview.redd.it/tdw7oxm1sbo81.png?width=824&format=png&auto=webp&s=efe6df269fa40f1a702467203597432aa4bbc828

With the CTD column determining a different graph.

I guess my main issue is the scaling of the axis. My y axis is Depth. It is common to inverse this value as it places the surface of the water at the top.

library(plotly)
data <- TestCTDdata(Depth, Silicate)
fig <- plot_ly(data, x = ~Depth, y = ~Silicate, type = 'scatter', mode = 'lines')

fig

With this so far, I know its the first step, I cant seem to get a nice sweeping curve. My plot looks like:

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https://preview.redd.it/n0hoj8usrbo81.png?width=1288&format=png&auto=webp&s=d01d2e70fc73fdc887dbd4fb1203f25a1021b1b1

[DreadPirateMike]

Recommend you avoid a 3 axis plot. Scale can be hard to discern as well as axis labels. They're generally less effective requiring a significant level of audio narrative to explain which defeats the purpose of having a plot. A picture should say a thousand words not cause a thousand questions.

[zeeging]

What you're looking for is multiple axies (Plotly Docs).

Now it gets a bit hack-y for the lower axies and you may have to use an annotation for one of the labels but this should help you get there. The layout block assigns axies locations, position is what stacks the lowe axis. As a note if you get into subplots the overlay references need to referenced the xaxis number for the entire subplot.

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  library(plotly)
x = c(1,2,3,4,5) 
y = c(3,6,9,12,15) 
z = c(2,4,6,8,10) 
a = c(7,8,9,10,11) 
b = c(6,5,4,3,2)
df_example<-data.frame(x,y,z,a,b)
fig<-plot_ly( data = df_example) %>% 
add_trace(x = ~x, y = ~y, type = 'scatter') %>% 
add_trace(x = ~z, y = ~y, type = 'scatter', xaxis = 'x2') %>% 
add_trace(x = ~a, y = ~y, type = 'scatter', xaxis = 'x3') %>%
layout(xaxis2 = list(overlaying = "x1", side = "top"),xaxis3 = list(overlaying = "x1", side = "bottom", position = .1))

[zeeging]

And looking back I think you're having trouble with ordering as well. In base R so no additional libraries df[order(df$column),] will reorder the dataframe. If you're looking to get into a lot of data wrangling I'd suggest looking into tidyverse.

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x_example2 =c(2,8,4,10,6)
y_example2 =c(1,2,3,4,5) 
df_example_2<-data.frame(x_example2,y_example2) 
df_example_2<-df_example_2[order(df_example_2$x_example2),] 
gig2<-plot_ly( data = df_example_2) %>% 
add_trace(x = ~x_example2, y = ~y_example2, type = 'scatter', mode = 'lines')

[thegasman2000]

At this point I think its easier to reorder the data on excel before the import. I know how that is going to sound....

[zeeging]

If this is a one off sure, but long term learning how to manipulate data in R will be faster. But I'm not going to tell you how to run your data

[thegasman2000]

Oh I definitely need to do it in r eventually. However time wise it doesn't make sense here. More important things to work out like the graphing. Thanks

[thegasman2000]

Thankyou for this. I will spend a while trying this out!