Merge pull request #585 from Kaggle/category_encoders_from_git · feibyte/docker-python@6a11b97 · GitHub

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Commit 6a11b97

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Philmod

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Merge pull request Kaggle#585 from Kaggle/category_encoders_from_git

Install category_encoders from GitHub

2 parents 1427897 + edfc261 commit 6a11b97
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+18-1Lines changed: 18 additions & 1 deletion

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  • test_category_encoders.py

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‎Dockerfile‎

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+2-1Lines changed: 2 additions & 1 deletion

Original file line number	Diff line number	Diff line change
@@ -346,7 +346,8 @@ RUN pip install --upgrade cython && \
346	346	pip install fasttext && \
347	347	apt-get install -y libhunspell-dev && pip install hunspell && \
348	348	pip install annoy && \
349		- pip install category_encoders && \
	349	+ # Need to use CountEncoder from category_encoders before it's officially released
	350	+ pip install git+https://github.com/scikit-learn-contrib/categorical-encoding.git && \
350	351	# Newer version crashes (latest = 1.14.0) when running tensorflow.
351	352	# python -c "from google.cloud import bigquery; import tensorflow". This flow is common because bigquery is imported in kaggle_gcp.py
352	353	# which is loaded at startup.

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‎tests/test_category_encoders.py‎

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+16Lines changed: 16 additions & 0 deletions

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@@ -0,0 +1,16 @@
	1	+ import unittest
	2	+
	3	+ ## Need to make sure we have CountEncoder available from the category_encoders library
	4	+ class TestCategoryEncoders(unittest.TestCase):
	5	+ def test_count_encoder(self):
	6	+
	7	+ from category_encoders import CountEncoder
	8	+ import pandas as pd
	9	+
	10	+ encoder = CountEncoder(cols="data")
	11	+
	12	+ data = pd.DataFrame([1, 2, 3, 1, 4, 5, 3, 1], columns=["data"])
	13	+
	14	+ encoded = encoder.fit_transform(data)
	15	+ self.assertTrue((encoded.data == [3, 1, 2, 3, 1, 1, 2, 3]).all())
	16	+

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