Also, I meant read_csv:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html
not load_csv
On Tue, Dec 16, 2014 at 9:55 AM, Daniel Sullivan
wrote:
>
> Hi Roberto,
>
> One thing you might try to get an integer instead of one-hot encoded
> values is a LabelEncoder:
Hi Roberto,
One thing you might try to get an integer instead of one-hot encoded values
is a LabelEncoder:
http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html
It's really useful if you process the complete dataset in memory. If you
can't hold your complete da
When using OneHotEncoder, is it possible to have one integer per feature as the
output, as opposed to binary representation?
Also, when using OneHotEncoder, what would be the method to load data (.csv)
with mixed type (number and categorical)?
Thanks,
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