speed up pandas calculation

Skip Montanaro skip.montanaro at gmail.com
Thu Jul 31 01:57:46 CEST 2014


> df = pd.read_csv('nhamcsopd2010.csv' , index_col='PATCODE',
low_memory=False)
> col_init = list(df.columns.values)
> keep_col = ['PATCODE', 'PATWT', 'VDAY', 'VMONTH', 'VYEAR', 'MED1',
'MED2', 'MED3', 'MED4', 'MED5']
> for col in col_init:
>     if col not in keep_col:
>         del df[col]

I'm no pandas expert, but a couple things come to mind. First, where is
your code slow (profile it, even with a few well-placed prints)? If it's in
read_csv there might be little you can do unless you load those data
repeatedly, and can save a pickled data frame as a caching measure. Second,
you loop over columns deciding one by one whether to keep or toss a column.
Instead try

df = df[keep_col]

Third, if deleting those other columns is costly, can you perhaps just
ignore them?

Can't be more investigative right now. I don't have pandas on Android. :-)

Skip
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