This is my data
degree, value
0.0,0.42105263157894735
1.0,0.47368421052631576
2.0,0.47368421052631576
3.0,0.47368421052631576
4.0,0.5
5.0,0.5
6.0,0.5
7.0,0.47368421052631576
8.0,0.47368421052631576
9.0,0.47368421052631576
10.0,0.39473684210526316
..............
350.0,0.5263157894736842
351.0,0.5526315789473685
352.0,0.47368421052631576
353.0,0.47368421052631576
354.0,0.47368421052631576
355.0,0.4473684210526316
356.0,0.4473684210526316
357.0,0.4473684210526316
358.0,0.42105263157894735
359.0,0.42105263157894735
So, it is circle from 0 to 359 degrees.
I want to build moving average using these values. I do it with:
df['smoothing'] = df['value'].rolling(window=10).mean()
degree value smoothed
0 0.0 0.526316 NaN
1 1.0 0.000000 NaN
2 2.0 0.000000 NaN
3 3.0 0.000000 NaN
4 4.0 0.000000 NaN
.. ... ... ...
355 355.0 0.000000 0.000000
356 356.0 0.447368 0.044737
357 357.0 0.500000 0.094737
358 358.0 0.526316 0.147368
359 359.0 0.500000 0.197368
But there is a problem: I loose values from 0 to 9. They are important for me.
So, my script must use degrees 351,352,353,354,355 and so on to count average for degrees 0,1,2,3....
I expect output:
degree value smoothed
0 0.0 0.526316 mean value of 351-0 degrees
1 1.0 0.000000 mean value of 352-1 degrees
2 2.0 0.000000 mean value of 353-2 degrees
3 3.0 0.000000 mean value of 354-3 degrees
4 4.0 0.000000 mean value of 355-4 degrees
................
and so on
How to do it? Thank you.
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