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How to Calculate Rolling Correlation in R?
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How to Calculate Rolling Correlation in Python?

Last Updated : 29 Jan, 2022
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Correlation generally determines the relationship between two variables. The rolling correlation measure the correlation between two-time series data on a rolling window Rolling correlation can be applied to a specific window width to determine short-term correlations. 

Calculating Rolling Correlation in Python

Let's use sales data of two products A and B in the last 60 months to calculate the rolling correlation. Pandas package provides a function called rolling.corr() to calculate the rolling correlation.

Syntax:

data1.rolling(width).corr(data2)

Where, 

  • data1, data2 - data/column of interest (type series)
  • width - Rolling window width (int)

Note: The width of the rolling window should be 3 or greater in order to calculate correlations.

Data Used:  

Python3 
# import pandas module import pandas as pd  # read the data data = pd.read_csv('product_sales.csv')  # display top 10 rows print(data.head(10))  # display column names print(data.columns)

Output:

Example 2:

Here, we used the window width of 6, which shows the successive 6 months rolling correlation. We could see a significant correlation between two products sales any sudden dip or rise in correlation signals an unusual event, that caused the dip.

Python3 
data['Product A'].rolling(6).corr(data['Product B'])  # formatting the output k = 1 for i, j in enumerate(data['Product A'].rolling(6).corr(data['Product B'])):     if (i >= 5 and i < 12):         print(f'The correlation in sales during months\         {k} through {i+1} is {j}')         i = 0         k += 1

Output:

Now's let us try the same for 3-month correlation as shown below,

Example 3:

Python3 
data['Product A'].rolling(3).corr(data['Product B'])  # formatting the output k = 1 for i, j in enumerate(data['Product A'].rolling(3).corr(data['Product B'])):     if (i >= 3 and i < 12):         print(             f'The correlation in sales during months {k} \             through {i+1} is {j}')         i = 0         k += 1

Output:


Next Article
How to Calculate Rolling Correlation in R?

J
jssuriyakumar
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Article Tags :
  • Python
  • Python-pandas
Practice Tags :
  • python

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