How to filter a struct array in a spark dataframe?

Question

I have the following code and outputs.

import org.apache.spark.sql.functions.{collect_list, struct}
import sqlContext.implicits._

val df = Seq(
  ("john", "tomato", 1.99),
  ("john", "carrot", 0.45),
  ("bill", "apple", 0.99),
  ("john", "banana", 1.29),
  ("bill", "taco", 2.59)
).toDF("name", "food", "price")

df.groupBy($"name")
  .agg(collect_list(struct($"food", $"price")).as("foods"))
  .show(false)

df.printSchema

Output and Schema:

+----+---------------------------------------------+
|name|foods                                        |
+----+---------------------------------------------+
|john|[[tomato,1.99], [carrot,0.45], [banana,1.29]]|
|bill|[[apple,0.99], [taco,2.59]]                  |
+----+---------------------------------------------+

root
 |-- name: string (nullable = true)
 |-- foods: array (nullable = false)
 |    |-- element: struct (containsNull = false)
 |    |    |-- food: string (nullable = true)
 |    |    |-- price: double (nullable = false)

I want to filter based on df("foods.price") > 1.00. How do I filter this to get the output below?

+----+---------------------------------------------+
|name|foods                                        |
+----+---------------------------------------------+
|john|[[banana,1.29], [tomato,1.99]]               |
|bill|[[[taco,2.59]]                               |
+----+---------------------------------------------+

I have tried df.filter($"foods.food" > 1.00), but this does not work as I'm getting an error. Anything else I can try?