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I have 3 process parameters that independently cycle between zero and some peak value, as shown on this filled line time-series plot: enter image description here

Although not a direct control variable, the 'health' of the system can be gauged by the consistency of relative 'stagger' (or difference) between these three parameters at any single point in time. A-B, B-C, C-A.

I am struggling to find an effective way to represent these relative stagger values - on the same timeline. A simple plot of e.g. A - B cycles positive to negative but isn't very intuitive. Ideally I'd like to represent all three relative differences on one discernible plot.

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You could compare the relative values over time quite easily with a "stacked" graph, where each of the processes is a layer in the stack. In Pandas' plotting, it is referred to as an area plot.

Here is an example with some dummy data:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

p1, p2, p3 = np.random.random(100), np.random.random(100), np.random.random(100)

df = pd.DataFrame([p1, p2, p3]).T
df.head(2)
# output
#              0         1         2
#    0  0.542490  0.099974  0.831589
#    1  0.988922  0.035026  0.752813

df.plot(kind="area", stacked=True); plt.show()

stacked/area plot

I think this might allow you to see the relative swings in each of the processes quite clearly - you could also shift the slightly to be in phase, which will make things easier.

| improve this answer | |
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  • $\begingroup$ Perfect - just checked Plotly Filled Area and I think it will do the job - even representing when the difference switches positive to negative. Many thanks :) $\endgroup$ – MarkMyWords Mar 31 at 14:26

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