Thank for your advice. I thought that wasn't necessary post also example code. So, I report the python script to plot a histogram with its kde. At bottom there is link to see the output.

Blockquote

import numpy as np

import pandas as pd

from scipy import stats

import matplotlib.pyplot as plt

import numpy as np

%matplotlib inline

"""array_1 contains 102 values each of which between 0 and 1"""

array_1 = [0.8, 0.9, 0.78, 0.97, 0.87, 0.78, 0.89, 0.83, 0.97, 0.95, 0.87, 0.95, 0.92, 0.78, 0.92, 0.92, 0.95, 0.92, 0.77, 0.74, 0.73, 0.76, 0.74, 0.93, 0.8, 0.83, 0.78, 0.79, 0.83, 0.82, 0.82, 0.77, 0.75, 0.79, 0.77, 0.74, 0.82 ...]

kde = stats.gaussian_kde(array_1)

xx = np.linspace(0, 1, 102)

plt, ax = plt.subplots(figsize = (10, 10))

ax.xaxis.set_tick_params(labelsize = 20)

ax.yaxis.set_tick_params(labelsize = 20)

ax.set_title('Score distribution', fontsize = 30)

ax.set_xlabel('Score', fontsize = 22)

ax.set_ylabel('Density', fontsize = 22)

ax.hist(array_1, bins = 20, range = (0, 1), color = '#86b300', density=True, edgecolor='black', linewidth=1.2)

ax.plot(xx, kde(xx), linewidth = 3, color = '#1a3300')

Blockquote

Consider that I would a unique plot with only kdes. I would overlap another 11 kdes to that already existing. Another 11 arrays are similar to what I have reported above (named 'array_1').

Thank you so much