1B) Random-sampling.py
import numpy as np
N=10000
mu=10
std=2
population_df=np.random.normal(mu,std,N)
def random_sampling(df,n):
random_sample=np.random.choice(df,replace = False,size=n)
return(random_sample)
randomsample=random_sampling (population_df,N)
print(randomsample)


1D) Aggregation.py
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10,4)),
index = pd.date_range('1/1/2000',periods=10),
columns=['A','B','C','D']
print(df)
df=pd.DataFrame(np.random.randn(10,4),index = pd.date_range('1/1/2000',periods=10))
r=df.rolling(3,min_periods=1).sum()
print(r)