PySpark - How to extract information from a column of a Spark DataFrame in JSON format but of type String

I find myself working with PySpark and using the Spark DataFrame in which each row of the DataFrame contains this information (which will always be the same), although the values ​​inside "tree", "grass" and "weed" may vary ".

{tree={in_season=true, index={color=null, category=null, value=null}, display_name=Tree, data_available=false}, weed={in_season=false, index={color=null, category=null, value=null}, display_name=Weed, data_available=false}, grass={in_season=true, index={color=null, category=null, value=null}, display_name=Grass, data_available=false}}

What I'm trying to do is keep some fields, for example, from "tree", keep the fields "in_season", "index -> value", "display_name", among others.

The dataframe has the following schema:

df2.printSchema()

• data: map (nullable = true)
  • key: string
  • value: string (valueContainsNull = true)
• types: string (nullable = true)
• plants: string (nullable = true)

What I have tried so far is to use StructType() as follows:

schema = ArrayType(
    StructType([StructField("tree", StringType())]))

df3 = df2.withColumn("tree", from_json(df2.types, schema))

The result I am getting is NULL for each row of the dataframe.

Is there any other way to do this, or do I have to do it with the StructType in another way?

Thank you very much in advance for the help!