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Pandas Parallel Appy
from joblib import Parallel, delayed
def expesive_calc(df):
df['new_col'] = ...
return df
def apply_parallel(gdf, func):
ret_list = Parallel(n_jobs=8)(delayed(func)(group) for name, group in gdf)
return pd.concat(ret_list)
df = apply_parallel(df.groupby('grp'), expensive_calc)
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