Python Data Frame : simple string split that includes ‘-‘

Happy New Year everyone. I have a Dataframe with ints and strings in each column. In my string column, some of my values contain “-” in the middle, and I want to remove any strings after “-“. Take a look at my df below.

input:
    buzz_id     facet   facet_cls   facet_val   p_buzz_date
0   95713207    A3      Small           MN        20160101
1   95713207    S3      Small-box       Tbd       20160101
2   95713207    F1      Medium          es        20160101
3   95713207    A2      Medium-box      esf       20160101
4   95713207    A1      Dum-pal         ess       20160101
...

output:
    buzz_id     facet   facet_cls   facet_val   p_buzz_date
0   95713207    A3      Small           MN        20160101
1   95713207    S3      Small           Tbd       20160101
2   95713207    F1      Medium          es        20160101
3   95713207    A2      Medium          esf       20160101
4   95713207    A1      Dum             ess       20160101
...

So in my “facet_cls” column, anything after the “-” (including the “-“) needs to be removed. And my data itself is very large, so I want to use the fastest process I can find. Any ideas?

Thanks in advance!

Use >split and pass str[0] selects only the first value of the list:

df['facet_cls'] = df['facet_cls'].str.split('-').str[0]
print (df)
    buzz_id facet facet_cls facet_val  p_buzz_date
0  95713207    A3     Small        MN     20160101
1  95713207    S3     Small       Tbd     20160101
2  95713207    F1    Medium        es     20160101
3  95713207    A2    Medium       esf     20160101
4  95713207    A1       Dum       ess     20160101

Details:

print (df['facet_cls'].str.split('-'))
0          [Small]
1     [Small, box]
2         [Medium]
3    [Medium, box]
4       [Dum, pal]
Name: facet_cls, dtype: object