Find a block of steady column values
Can anyone give me a hint to speed up the following program? Situation: I
have a huge amount of measurement data. I need to extract data for "10
minutes stable operation conditions" of 5 parameters i.e. column values.
Here is my (working, but really slow) solution: - Take the first 10 rows
from the dataframe - Compare the min and max of each column to the first
value of the column - If at least one column min or max is not within
tolerance, delete the first row, repeat - If they are within tolerance,
calculate the mean of the results, store them, delete 10 rows, repeat. -
break when the dataframe has less than 10 rows
Since I am using a repeat loop, this takes 30min to extract 610 operation
points from 86.220 minutes of data.
Any help is appreciated. Thanks!
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