Moving average for python in 6 mins

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moving average is a commonly used technique in time series analysis to smooth out fluctuations in data and identify trends. it calculates the average of a set of data points within a specified window size. in python, you can easily compute the moving average using libraries like numpy or pandas.

here's a quick tutorial on how to calculate the moving average in python using pandas:

1. first, install the pandas library if you haven't already:


2. import the necessary libraries:


3. create a sample dataset:


4. calculate the moving average using the `rolling` method in pandas:


5. print the original data and the moving average:


here's the complete code example:



when you run this code, you'll see the original dataset along with the calculated moving average values based on the specified window size. you can adjust the `window_size` parameter to change the number of data points included in the moving average calculation.

this tutorial provides a basic example of calculating the moving average using pandas in python. you can further customize the code to suit your specific requirements and explore additional functionalities offered by pandas for time series analysis.

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