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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)
Release History

Release History

This version
History Node

0.0.1

Download Files

Download Files

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
dummipy-0.0.1-py2.7.egg (8.9 kB) Copy SHA256 Checksum SHA256 2.7 Egg May 18, 2015
dummipy-0.0.1.tar.gz (5.7 kB) Copy SHA256 Checksum SHA256 Source May 18, 2015

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