Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/2819#discussion_r19454162
--- Diff: docs/mllib-feature-extraction.md ---
@@ -95,8 +95,50 @@ tf.cache()
val idf = new IDF(minDocFreq = 2).fit(tf)
val tfidf: RDD[Vector] = idf.transform(tf)
{% endhighlight %}
+</div>
+<div data-lang="python" markdown="1">
+
+TF and IDF are implemented in
[HashingTF](api/python/pyspark.mllib.html#pyspark.mllib.feature.HashingTF)
+and [IDF](api/python/pyspark.mllib.html#pyspark.mllib.feature.IDF).
+`HashingTF` takes an RDD of list as the input.
+Each record could be an iterable of strings or other types.
+
+{% highlight python %}
+from pyspark import SparkContext
+from pyspark.mllib.linalg import Vector
--- End diff --
`Vector` is not used
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