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What tools can I use to make a visualization similar to this one? I want to have the mean be bolded and the standard deviation be shaded.

image

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The below piece of code will generate the following Image(your's is Subplotting Three of them, so you will get 3 different axe's and per axes you have to use fill-between) (Kindly ignore the Axis Label's..)

plt.style.use('ggplot') #Change/Remove This If you Want

fig, ax = plt.subplots(figsize=(8, 4))
ax.plot(trees_grid, train_acc.mean(axis=1), alpha=0.5, color='blue', label='train', linewidth = 4.0)
ax.plot(trees_grid, test_acc.mean(axis=1), alpha=0.5, color='red', label='cv', linewidth = 1.0)
ax.fill_between(trees_grid, test_acc.mean(axis=1) - test_acc.std(axis=1), test_acc.mean(axis=1) + test_acc.std(axis=1), color='#888888', alpha=0.4)
ax.fill_between(trees_grid, test_acc.mean(axis=1) - 2*test_acc.std(axis=1), test_acc.mean(axis=1) + 2*test_acc.std(axis=1), color='#888888', alpha=0.2)
ax.legend(loc='best')
ax.set_ylim([0.88,1.02])
ax.set_ylabel("Accuracy")
ax.set_xlabel("N_estimators")

enter image description here

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Use the seaborn plotting library for python, specifically seaborn.tsplot:

import seaborn as sns

gammas = sns.load_dataset("gammas")
ax = sns.tsplot(time="timepoint", value="BOLD signal",
                 unit="subject", condition="ROI",
                 data=gammas)

error plot

Note: tsplot() is deprecated as of seaborn version 0.9. It thus might be good to use some other way to plot the data.

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