Title: Rolling Time Window
Slug: rolling_time_windows
Summary: How to use rolling time windows in pandas for machine learning in Python.
Date: 2017-09-11 12:00
Category: Machine Learning
Tags: Preprocessing Dates And Times
Authors: Chris Albon

Preliminaries



In [1]:

    
# Load library
import pandas as pd

Create Date Data



In [2]:

    
# 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]

Create A Rolling Time Window Of Two Rows



In [3]:

    
# Calculate rolling mean
df.rolling(window=2).mean()









    Out[3]:







  
    
      
      Stock_Price
    
  
  
    
      2010-01-31
      NaN
    
    
      2010-02-28
      1.5
    
    
      2010-03-31
      2.5
    
    
      2010-04-30
      3.5
    
    
      2010-05-31
      4.5



In [4]:

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









    Out[4]:







  
    
      
      Stock_Price
    
  
  
    
      2010-01-31
      NaN
    
    
      2010-02-28
      2.0
    
    
      2010-03-31
      3.0
    
    
      2010-04-30
      4.0
    
    
      2010-05-31
      5.0

	Stock_Price
2010-01-31	NaN
2010-02-28	1.5
2010-03-31	2.5
2010-04-30	3.5
2010-05-31	4.5