diff options
author | Xusen Yin <yinxusen@gmail.com> | 2015-12-09 12:00:48 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-12-09 12:00:48 -0800 |
commit | 051c6a066f7b5fcc7472412144c15b50a5319bd5 (patch) | |
tree | 810e743d0bd63ec07818e57d51469238e0998564 /examples/src/main/python | |
parent | 1eb7c22ce72a1b82ed194a51bbcf0da9c771605a (diff) | |
download | spark-051c6a066f7b5fcc7472412144c15b50a5319bd5.tar.gz spark-051c6a066f7b5fcc7472412144c15b50a5319bd5.tar.bz2 spark-051c6a066f7b5fcc7472412144c15b50a5319bd5.zip |
[SPARK-11551][DOC] Replace example code in ml-features.md using include_example
PR on behalf of somideshmukh, thanks!
Author: Xusen Yin <yinxusen@gmail.com>
Author: somideshmukh <somilde@us.ibm.com>
Closes #10219 from yinxusen/SPARK-11551.
Diffstat (limited to 'examples/src/main/python')
-rw-r--r-- | examples/src/main/python/ml/binarizer_example.py | 43 | ||||
-rw-r--r-- | examples/src/main/python/ml/bucketizer_example.py | 43 | ||||
-rw-r--r-- | examples/src/main/python/ml/elementwise_product_example.py | 39 | ||||
-rw-r--r-- | examples/src/main/python/ml/n_gram_example.py | 42 | ||||
-rw-r--r-- | examples/src/main/python/ml/normalizer_example.py | 43 | ||||
-rw-r--r-- | examples/src/main/python/ml/onehot_encoder_example.py | 48 | ||||
-rw-r--r-- | examples/src/main/python/ml/pca_example.py | 42 | ||||
-rw-r--r-- | examples/src/main/python/ml/polynomial_expansion_example.py | 43 | ||||
-rw-r--r-- | examples/src/main/python/ml/rformula_example.py | 44 | ||||
-rw-r--r-- | examples/src/main/python/ml/standard_scaler_example.py | 43 | ||||
-rw-r--r-- | examples/src/main/python/ml/stopwords_remover_example.py | 40 | ||||
-rw-r--r-- | examples/src/main/python/ml/string_indexer_example.py | 39 | ||||
-rw-r--r-- | examples/src/main/python/ml/tokenizer_example.py | 44 | ||||
-rw-r--r-- | examples/src/main/python/ml/vector_assembler_example.py | 42 | ||||
-rw-r--r-- | examples/src/main/python/ml/vector_indexer_example.py | 40 |
15 files changed, 635 insertions, 0 deletions
diff --git a/examples/src/main/python/ml/binarizer_example.py b/examples/src/main/python/ml/binarizer_example.py new file mode 100644 index 0000000000..317cfa638a --- /dev/null +++ b/examples/src/main/python/ml/binarizer_example.py @@ -0,0 +1,43 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import Binarizer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="BinarizerExample") + sqlContext = SQLContext(sc) + + # $example on$ + continuousDataFrame = sqlContext.createDataFrame([ + (0, 0.1), + (1, 0.8), + (2, 0.2) + ], ["label", "feature"]) + binarizer = Binarizer(threshold=0.5, inputCol="feature", outputCol="binarized_feature") + binarizedDataFrame = binarizer.transform(continuousDataFrame) + binarizedFeatures = binarizedDataFrame.select("binarized_feature") + for binarized_feature, in binarizedFeatures.collect(): + print(binarized_feature) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/bucketizer_example.py b/examples/src/main/python/ml/bucketizer_example.py new file mode 100644 index 0000000000..4304255f35 --- /dev/null +++ b/examples/src/main/python/ml/bucketizer_example.py @@ -0,0 +1,43 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import Bucketizer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="BucketizerExample") + sqlContext = SQLContext(sc) + + # $example on$ + splits = [-float("inf"), -0.5, 0.0, 0.5, float("inf")] + + data = [(-0.5,), (-0.3,), (0.0,), (0.2,)] + dataFrame = sqlContext.createDataFrame(data, ["features"]) + + bucketizer = Bucketizer(splits=splits, inputCol="features", outputCol="bucketedFeatures") + + # Transform original data into its bucket index. + bucketedData = bucketizer.transform(dataFrame) + bucketedData.show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/elementwise_product_example.py b/examples/src/main/python/ml/elementwise_product_example.py new file mode 100644 index 0000000000..c85cb0d895 --- /dev/null +++ b/examples/src/main/python/ml/elementwise_product_example.py @@ -0,0 +1,39 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import ElementwiseProduct +from pyspark.mllib.linalg import Vectors +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="ElementwiseProductExample") + sqlContext = SQLContext(sc) + + # $example on$ + data = [(Vectors.dense([1.0, 2.0, 3.0]),), (Vectors.dense([4.0, 5.0, 6.0]),)] + df = sqlContext.createDataFrame(data, ["vector"]) + transformer = ElementwiseProduct(scalingVec=Vectors.dense([0.0, 1.0, 2.0]), + inputCol="vector", outputCol="transformedVector") + transformer.transform(df).show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/n_gram_example.py b/examples/src/main/python/ml/n_gram_example.py new file mode 100644 index 0000000000..f2d85f53e7 --- /dev/null +++ b/examples/src/main/python/ml/n_gram_example.py @@ -0,0 +1,42 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import NGram +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="NGramExample") + sqlContext = SQLContext(sc) + + # $example on$ + wordDataFrame = sqlContext.createDataFrame([ + (0, ["Hi", "I", "heard", "about", "Spark"]), + (1, ["I", "wish", "Java", "could", "use", "case", "classes"]), + (2, ["Logistic", "regression", "models", "are", "neat"]) + ], ["label", "words"]) + ngram = NGram(inputCol="words", outputCol="ngrams") + ngramDataFrame = ngram.transform(wordDataFrame) + for ngrams_label in ngramDataFrame.select("ngrams", "label").take(3): + print(ngrams_label) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/normalizer_example.py b/examples/src/main/python/ml/normalizer_example.py new file mode 100644 index 0000000000..d490221474 --- /dev/null +++ b/examples/src/main/python/ml/normalizer_example.py @@ -0,0 +1,43 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import Normalizer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="NormalizerExample") + sqlContext = SQLContext(sc) + + # $example on$ + dataFrame = sqlContext.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt") + + # Normalize each Vector using $L^1$ norm. + normalizer = Normalizer(inputCol="features", outputCol="normFeatures", p=1.0) + l1NormData = normalizer.transform(dataFrame) + l1NormData.show() + + # Normalize each Vector using $L^\infty$ norm. + lInfNormData = normalizer.transform(dataFrame, {normalizer.p: float("inf")}) + lInfNormData.show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/onehot_encoder_example.py b/examples/src/main/python/ml/onehot_encoder_example.py new file mode 100644 index 0000000000..0f94c26638 --- /dev/null +++ b/examples/src/main/python/ml/onehot_encoder_example.py @@ -0,0 +1,48 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import OneHotEncoder, StringIndexer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="OneHotEncoderExample") + sqlContext = SQLContext(sc) + + # $example on$ + df = sqlContext.createDataFrame([ + (0, "a"), + (1, "b"), + (2, "c"), + (3, "a"), + (4, "a"), + (5, "c") + ], ["id", "category"]) + + stringIndexer = StringIndexer(inputCol="category", outputCol="categoryIndex") + model = stringIndexer.fit(df) + indexed = model.transform(df) + encoder = OneHotEncoder(dropLast=False, inputCol="categoryIndex", outputCol="categoryVec") + encoded = encoder.transform(indexed) + encoded.select("id", "categoryVec").show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/pca_example.py b/examples/src/main/python/ml/pca_example.py new file mode 100644 index 0000000000..a17181f1b8 --- /dev/null +++ b/examples/src/main/python/ml/pca_example.py @@ -0,0 +1,42 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import PCA +from pyspark.mllib.linalg import Vectors +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="PCAExample") + sqlContext = SQLContext(sc) + + # $example on$ + data = [(Vectors.sparse(5, [(1, 1.0), (3, 7.0)]),), + (Vectors.dense([2.0, 0.0, 3.0, 4.0, 5.0]),), + (Vectors.dense([4.0, 0.0, 0.0, 6.0, 7.0]),)] + df = sqlContext.createDataFrame(data, ["features"]) + pca = PCA(k=3, inputCol="features", outputCol="pcaFeatures") + model = pca.fit(df) + result = model.transform(df).select("pcaFeatures") + result.show(truncate=False) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/polynomial_expansion_example.py b/examples/src/main/python/ml/polynomial_expansion_example.py new file mode 100644 index 0000000000..3d4fafd1a4 --- /dev/null +++ b/examples/src/main/python/ml/polynomial_expansion_example.py @@ -0,0 +1,43 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import PolynomialExpansion +from pyspark.mllib.linalg import Vectors +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="PolynomialExpansionExample") + sqlContext = SQLContext(sc) + + # $example on$ + df = sqlContext\ + .createDataFrame([(Vectors.dense([-2.0, 2.3]), ), + (Vectors.dense([0.0, 0.0]), ), + (Vectors.dense([0.6, -1.1]), )], + ["features"]) + px = PolynomialExpansion(degree=2, inputCol="features", outputCol="polyFeatures") + polyDF = px.transform(df) + for expanded in polyDF.select("polyFeatures").take(3): + print(expanded) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/rformula_example.py b/examples/src/main/python/ml/rformula_example.py new file mode 100644 index 0000000000..b544a14700 --- /dev/null +++ b/examples/src/main/python/ml/rformula_example.py @@ -0,0 +1,44 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import RFormula +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="RFormulaExample") + sqlContext = SQLContext(sc) + + # $example on$ + dataset = sqlContext.createDataFrame( + [(7, "US", 18, 1.0), + (8, "CA", 12, 0.0), + (9, "NZ", 15, 0.0)], + ["id", "country", "hour", "clicked"]) + formula = RFormula( + formula="clicked ~ country + hour", + featuresCol="features", + labelCol="label") + output = formula.fit(dataset).transform(dataset) + output.select("features", "label").show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/standard_scaler_example.py b/examples/src/main/python/ml/standard_scaler_example.py new file mode 100644 index 0000000000..ae7aa85005 --- /dev/null +++ b/examples/src/main/python/ml/standard_scaler_example.py @@ -0,0 +1,43 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import StandardScaler +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="StandardScalerExample") + sqlContext = SQLContext(sc) + + # $example on$ + dataFrame = sqlContext.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt") + scaler = StandardScaler(inputCol="features", outputCol="scaledFeatures", + withStd=True, withMean=False) + + # Compute summary statistics by fitting the StandardScaler + scalerModel = scaler.fit(dataFrame) + + # Normalize each feature to have unit standard deviation. + scaledData = scalerModel.transform(dataFrame) + scaledData.show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/stopwords_remover_example.py b/examples/src/main/python/ml/stopwords_remover_example.py new file mode 100644 index 0000000000..01f94af8ca --- /dev/null +++ b/examples/src/main/python/ml/stopwords_remover_example.py @@ -0,0 +1,40 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import StopWordsRemover +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="StopWordsRemoverExample") + sqlContext = SQLContext(sc) + + # $example on$ + sentenceData = sqlContext.createDataFrame([ + (0, ["I", "saw", "the", "red", "baloon"]), + (1, ["Mary", "had", "a", "little", "lamb"]) + ], ["label", "raw"]) + + remover = StopWordsRemover(inputCol="raw", outputCol="filtered") + remover.transform(sentenceData).show(truncate=False) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/string_indexer_example.py b/examples/src/main/python/ml/string_indexer_example.py new file mode 100644 index 0000000000..58a8cb5d56 --- /dev/null +++ b/examples/src/main/python/ml/string_indexer_example.py @@ -0,0 +1,39 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import StringIndexer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="StringIndexerExample") + sqlContext = SQLContext(sc) + + # $example on$ + df = sqlContext.createDataFrame( + [(0, "a"), (1, "b"), (2, "c"), (3, "a"), (4, "a"), (5, "c")], + ["id", "category"]) + indexer = StringIndexer(inputCol="category", outputCol="categoryIndex") + indexed = indexer.fit(df).transform(df) + indexed.show() + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/tokenizer_example.py b/examples/src/main/python/ml/tokenizer_example.py new file mode 100644 index 0000000000..ce9b225be5 --- /dev/null +++ b/examples/src/main/python/ml/tokenizer_example.py @@ -0,0 +1,44 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import Tokenizer, RegexTokenizer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="TokenizerExample") + sqlContext = SQLContext(sc) + + # $example on$ + sentenceDataFrame = sqlContext.createDataFrame([ + (0, "Hi I heard about Spark"), + (1, "I wish Java could use case classes"), + (2, "Logistic,regression,models,are,neat") + ], ["label", "sentence"]) + tokenizer = Tokenizer(inputCol="sentence", outputCol="words") + wordsDataFrame = tokenizer.transform(sentenceDataFrame) + for words_label in wordsDataFrame.select("words", "label").take(3): + print(words_label) + regexTokenizer = RegexTokenizer(inputCol="sentence", outputCol="words", pattern="\\W") + # alternatively, pattern="\\w+", gaps(False) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/vector_assembler_example.py b/examples/src/main/python/ml/vector_assembler_example.py new file mode 100644 index 0000000000..04f64839f1 --- /dev/null +++ b/examples/src/main/python/ml/vector_assembler_example.py @@ -0,0 +1,42 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.mllib.linalg import Vectors +from pyspark.ml.feature import VectorAssembler +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="VectorAssemblerExample") + sqlContext = SQLContext(sc) + + # $example on$ + dataset = sqlContext.createDataFrame( + [(0, 18, 1.0, Vectors.dense([0.0, 10.0, 0.5]), 1.0)], + ["id", "hour", "mobile", "userFeatures", "clicked"]) + assembler = VectorAssembler( + inputCols=["hour", "mobile", "userFeatures"], + outputCol="features") + output = assembler.transform(dataset) + print(output.select("features", "clicked").first()) + # $example off$ + + sc.stop() diff --git a/examples/src/main/python/ml/vector_indexer_example.py b/examples/src/main/python/ml/vector_indexer_example.py new file mode 100644 index 0000000000..146f41c1dd --- /dev/null +++ b/examples/src/main/python/ml/vector_indexer_example.py @@ -0,0 +1,40 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from __future__ import print_function + +from pyspark import SparkContext +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import VectorIndexer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="VectorIndexerExample") + sqlContext = SQLContext(sc) + + # $example on$ + data = sqlContext.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt") + indexer = VectorIndexer(inputCol="features", outputCol="indexed", maxCategories=10) + indexerModel = indexer.fit(data) + + # Create new column "indexed" with categorical values transformed to indices + indexedData = indexerModel.transform(data) + indexedData.show() + # $example off$ + + sc.stop() |