Categorical variable friendly pandas data frames
Project description
Quickstart
$ pip install dummipy
Let it out of the box…
from sklearn.linear_model import LinearRegression from dummipy import cereal type(cereal) # CategoricalDataFrame cereal.head() reg = LinearRegression() reg.fit(cereal[['mfr', 'vitamins', 'fat']], cereal.calories)
Installation
You’ll need `pandas <http://pandas.pydata.org/>`__, but any old version will do the trick. There is no pandas version pegged in the setup.py file so installing dummipy won’t mess up your existing sci-py setup.
$ pip install dummipy
Use
Just use it like any old data frame. That’s really all there is to it.
import dummipy as dp df = dp.CategoricalDataFrame({ "x": range(5), "y": ["a", "b", "c", "a", "b"] }) df = pd.read_csv("foo.csv") df = dp.CategoricalDataFrame(df)
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