Pandas parallelize for loop

import multiprocessing as mp
pool = mp.Pool(processes=mp.cpu_count())

def func( arg ):
    idx,row = arg
	# Edit df
    return row

new_rows = pool.map( func, [(idx,row) for idx,row in data_all.iterrows()])
data_all_new = pd.concat( new_rows )

Source: stackoverflow.com

Similar codes

1 vote110 views1 answer
Extract first letter of column python
Python
0 vote107 views1 answer
Python lvl up
Python
7 votes114 views3 answers
Python calendar
Python
0 vote117 views1 answer
Fast input python
Python
0 vote158 views1 answer
Django pull from Google Sheets
Python Django
0 vote159 views1 answer
Difference between __gte and __lte in Django
Python Django
1 vote106 views1 answer
Python get current number of threads
Python
0 vote124 views1 answer
How to save all countries from a list in a database python
Python
0 vote120 views1 answer
Launching tensorboard from a python script
Python
1 vote109 views1 answer
Reject invalid input using a loop in python
Python