In Spark-scala, how to fill Vectors.dense in DataFrame from CSV?

[Dan Bikle]

hello spark-world,

I am new to spark.

I noticed this online example:

http://spark.apache.org/docs/latest/ml-pipeline.html

I am curious about this syntax:

    // Prepare training data from a list of (label, features) tuples.
    val training = spark.createDataFrame(Seq(
      (1.0, Vectors.dense(0.0, 1.1, 0.1)),
      (0.0, Vectors.dense(2.0, 1.0, -1.0)),
      (0.0, Vectors.dense(2.0, 1.3, 1.0)),
      (1.0, Vectors.dense(0.0, 1.2, -0.5))
    )).toDF("label", "features")

Is it possible to replace the above call to some syntax which reads values
from CSV?

I want something comparable to Python-Pandas read_csv() method.