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I have time-series data. 7200 rows(data point) and two columns (one time and one frequency data). I want to calculate the average of the frequencies for every 120 rows. I wrote the following code. I know it is very stupid, but I don't want to repeat the following code for 60 times. Is there any way in which I can do it automatically or shorter?

Thank you for your help

window1 = df1[['p1', 'p2']].iloc[0:119].mean(axis=0)
window2 = df1[['p1', 'p2']].iloc[120:239].mean(axis=0)
Chris
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Ali Soleymani
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  • Does this answer your question? [Calculate average of every x rows in a table and create new table](https://stackoverflow.com/questions/36810595/calculate-average-of-every-x-rows-in-a-table-and-create-new-table) – Chris Jan 15 '20 at 19:23
  • Have you taken a look at the pandas [rolling](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rolling.html) functionality? – totalhack Jan 15 '20 at 19:34

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