I have to plot two monthly maximum temperature timeseries to show the difference between them. How to go about doing it?

Question

I have two temperature timeseries showing maximum monthly temperature for 5 years with one being for 0 degree Celcius rise and one for 1 degree Celcius rise in the region (in terms of climate change). So, both the series are being used to show how the temperature is changing as the climate is changing and for that I need to make a graph like as shown in the image linked in the post. How do I do it in python specifically?

The graph in question is designed in a way in which one is the baseline curve and the other goes around it, but the differences in both the graph or the area in between both the graphs is shaded. I also tried using excel but that failed to do so. I know it can be done through python or any other coding language but have no idea on how to proceed as I don't know what kind of graph this is (Although I do know how to make line graphs among other basic things). Help from anyone with experience in making such a graph would be greatly appreciated.

This is the data series I have to plot

This is what the expected result should be

Python is the preferred language but I would also welcome solutions from google earth engine as I'm trying to be proficient in both.

I couldn't find any previous questions regarding this, maybe due to my inability to word the question correctly, so if you have any reference to past questions asked on this platform which may help would also be welcome.

Answer 1

The way to do this is to plot both curves on the same plot, and use Matplotlib's fill_between. You need to provide the x coordinates of the curves, the two sets of y coordinates for the two curves, and a condition specifying which bits to fill in with your chosen colour, e.g. where=temperature>=mean_temperature. You'll need to call fill_between twice to colour in two separate bits.

import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import uniform_filter1d

temperature = [np.sin(x) + np.random.normal(scale=2) for x in range(0,100)]
mean_temperature = uniform_filter1d(temperature, size=20)

fig, ax = plt.subplots(figsize=(12,5))
ax.plot(temperature, 'k')
ax.plot(mean_temperature, 'k')
ax.fill_between(range(0, len(temperature)), temperature, mean_temperature, where=temperature>=mean_temperature, interpolate=True, color="red")
ax.fill_between(range(0, len(temperature)), temperature, mean_temperature, where=temperature<mean_temperature, interpolate=True, color="blue")