Simple Time Series Data Smoothing of Python Panda Columns (By Group ID) and New Field Creation/Calculation
$10-30 USD
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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.
Nº del proyecto: #30177812
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4 freelancers están ofertando un promedio de $35 por este trabajo
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
Hi, there. You will get the perfect result, as i am an advanced python developer. I have much experience with python, django, Machine Learning. I would be delighted to work for you as this is something I am very exper Más
