apply OneHotEncoder for several categorical columns in SparkMlib

Question

I have several categorical features and would like to transform them all using OneHotEncoder. However, when I tried to apply the StringIndexer, there I

Answer 1

I think the above code will not give the same results as required. In the encoders section, there is required a little modification. Because, again the StringIndexer is applied on Indexers.So, that will results in the same results.

#In the following section:
encoders = [
    StringIndexer(
        inputCol=indexer.getOutputCol(),
        outputCol="{0}_encoded".format(indexer.getOutputCol())) 
    for indexer in indexers
]

#Replace the StringIndexer with OneHotEncoder as follows:
encoders = [OneHotEncoder(dropLast=False,inputCol=indexer.getOutputCol(),
            outputCol="{0}_encoded".format(indexer.getOutputCol())) 
            for indexer in indexers
]

Now, the complete code look like the following:

from pyspark.ml import Pipeline
from pyspark.ml.feature import StringIndexer, OneHotEncoder, VectorAssembler

categorical_columns= ['Gender', 'Age', 'Occupation', 'City_Category','Marital_Status']

# The index of string vlaues multiple columns
indexers = [
    StringIndexer(inputCol=c, outputCol="{0}_indexed".format(c))
    for c in categorical_columns
]

# The encode of indexed vlaues multiple columns
encoders = [OneHotEncoder(dropLast=False,inputCol=indexer.getOutputCol(),
            outputCol="{0}_encoded".format(indexer.getOutputCol())) 
    for indexer in indexers
]

# Vectorizing encoded values
assembler = VectorAssembler(inputCols=[encoder.getOutputCol() for encoder in encoders],outputCol="features")

pipeline = Pipeline(stages=indexers + encoders+[assembler])
model=pipeline.fit(data_df)
transformed = model.transform(data_df)
transformed.show(5)

For more details,please refer: visit:[1] https://spark.apache.org/docs/2.0.2/api/python/pyspark.ml.html#pyspark.ml.feature.StringIndexer visit:[2] https://spark.apache.org/docs/2.0.2/api/python/pyspark.ml.html#pyspark.ml.feature.OneHotEncoder.