## How to deal with Rolling Tine Window in Python 
def Kickstarter_Example_47():
    print()
    print(format('How to deal with Rolling Time Window in Python','*^82'))
    import warnings
    warnings.filterwarnings("ignore")

    # Load library
    import pandas as pd

    # Create datetimes
    time_index = pd.date_range('01/01/2010', periods=5, freq='M')

    # Create data frame, set index
    df = pd.DataFrame(index=time_index)

    # Create feature
    df['Stock_Price'] = [1,2,3,4,5]
    print(); print(df)

    # Create A Rolling Time Window Of Two Rows
    # Calculate rolling mean
    df1 = df.rolling(window=2).mean()
    print(); print(df1)

    # Identify max value in rolling time window
    df2 = df.rolling(window=2).max()
    print(); print(df2)

Kickstarter_Example_47()