Python - Probability Density Function & Cumulative Density Function, from sample vector of values

import numpy as npimport matplotlib.pyplot as pltfrom scipy.stats import norm
# Observationsobs = [
    0.4    , 0.4343    , 0.4571    , 0.48    , 0.5086    , 0.5543    , 0.5714    , 0.5943    , 0.6457    , 0.68    , 0.7086    , 0.7371    , 0.7543    , 0.8    , 0.8286    , 0.8514    , 0.8914    , 0.9086    , 0.9486    , 0.9829    , 1.0057    , 1.0229    , 1.0514    , 1.08    , 1.0914    , 1.12    , 1.1371    , 1.16    , 1.2    , 1.2229    , 1.28    , 1.2971    , 1.32    , 1.3429    , 1.3714    , 1.4171    , 1.44]
# Descriptive statisticsminimum = min(obs)
maximum = max(obs)
m = np.mean(obs, axis=None)
s = np.std(obs, axis=None)
# Debugprint "mean:", mprint "standard deviation:", sprint "cdf:", "\n", norm.cdf(obs, m, s)print "pdf:", "\n", norm.pdf(obs, m, s)
# Plot between min and max with .001 sized stepsx_axis = np.arange(minimum, maximum, 0.001)
plt.ylabel('Density')
plt.xlabel('Values')
plt.plot(x_axis, norm.pdf(x_axis, m, s))
plt.show()