text_plain_output_1.png image_output_1.png
from scipy.stats import expon

from scipy.stats import gamma

from scipy.stats import norm

from scipy.stats import uniform

import seaborn as sns

n = 10000
start = 10
width = 20
data_uniform = uniform.rvs(size=n, loc=start, scale=width)

ax = sns.distplot(data_uniform,
                  bins=100,
                  kde=True,
                  color='skyblue',
                  hist_kws={"linewidth": 15,'alpha':1})
ax.set(xlabel='Uniform Distribution ', ylabel='Frequency')

data_normal = norm.rvs(size=10000, loc=0, scale=1)

ax = sns.distplot(data_normal,
                  bins=100,
                  kde=True,
                  color='skyblue',
                  hist_kws={"linewidth": 15,'alpha':1})
ax.set(xlabel='Normal Distribution', ylabel='Frequency')

data_gamma = gamma.rvs(a=5, size=10000)

ax = sns.distplot(data_gamma,
                  kde=True,
                  bins=100,
                  color='skyblue',
                  hist_kws={"linewidth": 15,'alpha':1})
ax.set(xlabel='Gamma Distribution', ylabel='Frequency')

data_expon = expon.rvs(scale=1, loc=0, size=1000)

ax = sns.distplot(data_expon, kde=True, bins=100, color='skyblue', hist_kws={'linewidth': 15, 'alpha': 1})
ax.set(xlabel='Exponential Distribution', ylabel='Frequency')