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examples/src/main/python/ml/onehot_encoder_example.py
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HyukjinKwon
[SPARK-32138] Drop Python 2.7, 3.4 and 3.5
14 июл 2020, 05:22
14 июл 2020, 05:22
4ad9bfd
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# # 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. # # $example on$ from pyspark.ml.feature import OneHotEncoder # $example off$ from pyspark.sql import SparkSession if __name__ == "__main__": spark = SparkSession\ .builder\ .appName("OneHotEncoderExample")\ .getOrCreate() # Note: categorical features are usually first encoded with StringIndexer # $example on$ df = spark.createDataFrame([ (0.0, 1.0), (1.0, 0.0), (2.0, 1.0), (0.0, 2.0), (0.0, 1.0), (2.0, 0.0) ], ["categoryIndex1", "categoryIndex2"]) encoder = OneHotEncoder(inputCols=["categoryIndex1", "categoryIndex2"], outputCols=["categoryVec1", "categoryVec2"]) model = encoder.fit(df) encoded = model.transform(df) encoded.show() # $example off$ spark.stop()