Generating different types of data to illustrate examples or create a grid to conform to

expand_grid.py

# http://pandas.pydata.org/pandas-docs/stable/cookbook.html/ bottom example

def expand_grid(data_dict):
    rows = itertools.product(*data_dict.values())
    return pd.DataFrame.from_records(rows, columns=data_dict.keys())
  
df = expand_grid(
    {'height': [60, 70],
    'weight': [100, 140, 180],
    'sex': ['Male', 'Female']})

prob_distributions.py

from scipy import stats
import numpy as np

def plot_beta(a, b, res):
    x = np.linspace(stats.beta.ppf(0.01, a=a, b=b),
                  stats.beta.ppf(0.99, a=a, b=b), res)
    y = stats.beta.pdf(x, a, b)
    plt.plot(x, y)
  
def plot_poisson(mu):
    x = np.linspace(0,10,11)
    y = stats.poisson.pmf(x, mu=mu)
    plt.plot(x, y)

timeseries.py

# Add months to datetime
df['datetime'] + df['months_int'].values.astype('timedelta64[M]')

# Create DateTimeIndex
df = pd.DataFrame(index=pd.date_range('5/1/2015', periods=5))