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 vote203 views1 answer
Python division by zero
Python
0 vote194 views1 answer
Webdriver.chrome() python not working
Python
8 votes192 views1 answer
How to play a video in cv2
Python
-1 vote252 views1 answer
Convert .tif images files to .jpeg in python
Python
46 votes187 views6 answers
Comment in python
Python
2 votes255 views10 answers
Python turtle tutorial
Python
0 vote201 views1 answer
Add a constant to a list python
Python
2 votes274 views1 answer
Search code ascii python
Python
3 votes267 views2 answers
Pandas concat series into dataframe
Python
15 votes216 views3 answers
Divide list into equal parts python
Python