Independent project. Test file has data that I want to be grouped by the HAUL_ID field. I wish to apply a Hamming Filter (available in Numpy) using a window=25 to smooth the X and Y fields, but treat the smoothing independently for each HAUL_ID. The Date field can be used for the time series domain, obviously.
I then wish to create a new Field named SIN_Bearing, and calculate the field using the following formula:
SIN_Bearing = SIN(Bearing*(2*PI/360)). This step can be done on all the rows and does not need to be grouped by HAUL_ID first. Note, 'Bearing' is a field in the provided csv.
Finally export the results with all the original fields, the new smoothed XY fields, and the newly calculated SIN_Bearing field into a separate CSV file for each HAUL_ID. In this test file, there are 2 unique hauls - which of course should result in two files. For my later work I will have many more HAUL_IDs, and create additional field calculations. This will get me started.
I use Jupyter Notebook and Python3.
4 freelanceria on tarjonnut keskimäärin $35 tähän työhön
Hello, I am pandas expert. I can start right away. I understand your requirements completely. Groupby than apply the smoothing for each group independently. I can finish very fast. Best Regards, Borut