I am using Spark v3.0.0. My dataframe is:
indexer.show()
+------+--------+-----+
|row_id| city|index|
+------+--------+-----+
| 0|New York| 0.0|
| 1| Moscow| 3.0|
| 2| Beijing| 1.0|
| 3|New York| 0.0|
| 4| Paris| 2.0|
| 5| Paris| 2.0|
| 6|New York| 0.0|
| 7| Beijing| 1.0|
+------+--------+-----+
Then I want to use One hot encoding of the dataframe's column "index" and getting this error.
encoder = OneHotEncoder(inputCol="index", outputCol="encoding")
encoder.setDropLast(False)
indexer = encoder.transform(indexer)
----------------------------------------
AttributeErrorTraceback (most recent call last)
<ipython-input-32-70bbd67e6679> in <module>
1 encoder = OneHotEncoder(inputCol="index", outputCol="encoding")
2 encoder.setDropLast(False)
----> 3 indexer = encoder.transform(indexer)
AttributeError: 'OneHotEncoder' object has no attribute 'transform'
You need to fit it first - before fitting, the attribute does not exist indeed:
encoder = OneHotEncoder(inputCol="index", outputCol="encoding")
encoder.setDropLast(False)
ohe = encoder.fit(indexer) # indexer is the existing dataframe, see the question
indexer = ohe.transform(indexer)
See the example in the docs for more details on the usage.