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authorZheng RuiFeng <ruifengz@foxmail.com>2016-05-06 10:47:13 -0700
committerDavies Liu <davies.liu@gmail.com>2016-05-06 10:47:13 -0700
commit76ad04d9a0a7d4dfb762318d9c7be0d7720f4e1a (patch)
tree4aa03e2e1a2fb45eaf60ddb744551215780f01a9 /examples
parentfa928ff9a3c1de5d5aff9d14e6bc1bd03fcca087 (diff)
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[SPARK-14512] [DOC] Add python example for QuantileDiscretizer
## What changes were proposed in this pull request? Add the missing python example for QuantileDiscretizer ## How was this patch tested? manual tests Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #12281 from zhengruifeng/discret_pe.
Diffstat (limited to 'examples')
-rw-r--r--examples/src/main/python/ml/quantile_discretizer_example.py39
1 files changed, 39 insertions, 0 deletions
diff --git a/examples/src/main/python/ml/quantile_discretizer_example.py b/examples/src/main/python/ml/quantile_discretizer_example.py
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index 0000000000..6ae7bb18f8
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+++ b/examples/src/main/python/ml/quantile_discretizer_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
+
+# $example on$
+from pyspark.ml.feature import QuantileDiscretizer
+# $example off$
+from pyspark.sql import SparkSession
+
+
+if __name__ == "__main__":
+ spark = SparkSession.builder.appName("PythonQuantileDiscretizerExample").getOrCreate()
+
+ # $example on$
+ data = [(0, 18.0,), (1, 19.0,), (2, 8.0,), (3, 5.0,), (4, 2.2,)]
+ dataFrame = spark.createDataFrame(data, ["id", "hour"])
+
+ discretizer = QuantileDiscretizer(numBuckets=3, inputCol="hour", outputCol="result")
+
+ result = discretizer.fit(dataFrame).transform(dataFrame)
+ result.show()
+ # $example off$
+
+ spark.stop()