In one answer to: Is shared readonly data copied to different processes for multiprocessing? a working solution for shared memory for a numpy array is given.
How would the same look like if a pandas DataFrame should be used?
Background: I would like to be able to write to the DataFrame during multiprocessing and would like to be able to process it further after the multiprocessing has finished.
